Principal Engineer, Material Review Board (R5309)

🏢 Summary: Operational Safety Specialist role focused on aviation and UAS safety programs, including audits, investigations, CAPA management, safety metrics, and operational risk management across flight and ground operations. The position supports cross-functional safety initiatives and helps scale operational safety processes in a fast-paced defense technology environment. 🗂️ Requirements: Bachelor’s degree in engineering, safety, aviation, or related discipline, 3–5+ years of experience in aviation safety, flight operations, ground operations, UAS operations, or safety management systems, Familiarity with SMS principles, Experience with operational audits and mishap investigation processes, Ability to work across diverse operational environments and stakeholders, Strong analytical skills, Proficiency with safety or quality tracking systems, Strong written and verbal communication skills 📃 Skills: SMS, CAPA, HFACS, TapRooT, RCA, UAS, Aviation, Airworthiness, Safety, Auditing, Risk, Engineering 🏢 Description: Job Description: The Operational Safety Specialist plays a central role in strengthening both proactive and reactive safety programs across flight operations and ground environments. This position focuses on the execution and continuous improvement of auditing, safety metrics, investigations, and safety promotion activities spanning multiple aircraft programs. The role is instrumental in preparing safety programs for global scale and growth. You will work closely with Flight Safety, Ground Operations, Airworthiness, Engineering, EH&S, and Program teams to ensure operational hazards are identified early, tracked effectively, and addressed through closure. This position is ideal for someone who thrives in a fast-paced, dynamic environment; is detail-oriented; and brings strong analytical and communication skills to support the development of a world-class safety culture. What you'll do: - Conduct audits of ground procedures and operational practices across the enterprise to ensure compliance, identify gaps, and drive corrective actions. - Develop, maintain, and report leading and lagging safety metrics to drive transparency and continuous improvement. - Own and manage the Corrective and Preventive Action (CAPA) process, ensuring findings are logged, analyzed, assigned, and closed on schedule. - Lead the Safety Promotions program, including communications, awareness campaigns, and training touchpoints. - Lead medium- and lower-priority mishap and near-miss investigations, ensuring proper root cause analysis, documentation, and follow-through. - Maintain the Operational Risk Registry for the V-BAT platform and coordinate with engineering and operational stakeholders to ensure risks are properly assessed and updated. - Collaborate with Airworthiness and System Safety teams to align operational and engineering safety efforts. - Contribute to cross-functional safety reviews, readiness assessments, and operational approval activities. - Support customer reporting obligations and engagements related to operational safety performance. - Perform other duties as assigned. Required qualifications: - Bachelor’s degree in engineering, safety, aviation, or related discipline (or equivalent operational experience). - 3–5+ years of experience in aviation safety, flight or ground operations, UAS operations, or safety management systems. - Familiarity with SMS principles, operational audits, and mishap investigation processes. - Ability to work effectively across diverse operational environments with multiple stakeholders. - Strong analytical skills and proficiency with safety or quality tracking systems. - Strong written and verbal communication skills, particularly in producing investigation reports and safety summaries. Preferred qualifications: - Experience supporting UAS flight operations or military/rapid-deployment aviation environments. - Experience developing safety promotion or training materials. - Familiarity with risk management frameworks and operational assurance tools. - Formal training in mishap investigation methodologies (HFACS, TapRooT, RCA). - Experience with safety data analysis or safety-related software tools. - Demonstrated field experience supporting flightline or mission operations. Benefits: - Pay within range listed + Bonus + Benefits + Equity - Temporary employee package includes pay within range listed above and temporary benefits package after 60 days of employment. - Salary compensation is influenced by factors including skill set, experience, licenses and certifications, and work location. - All offers are contingent on a cleared background and possible reference check.

🏢 Summary: Senior Software Engineer role focused on building automation and observability solutions to enhance reliability across multi-data center AI infrastructure. The position combines strong programming skills with hands-on data center and Linux systems expertise to minimize downtime and optimize performance. It involves developing scalable services, improving monitoring and incident response, and collaborating across infrastructure and facility teams. 🗂️ Requirements: Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering or related field (or equivalent experience), 3+ years experience in SRE, Infrastructure, DevOps, or Systems Engineering in large-scale production environments, Strong production experience in Python, Solid Linux systems administration and kernel-level knowledge, Experience with containerization and orchestration (Docker, Kubernetes or similar), Experience implementing observability solutions (metrics, logging, tracing, monitoring, alerting), Understanding of networking fundamentals (TCP/IP, routing, DNS, redundancy), Experience troubleshooting distributed systems, hardware and network issues, Experience with on-call rotations and incident response practices (SLAs, error budgets), Ability to collaborate with cross-functional technical teams 📃 Skills: Python, Rust, Linux, Kubernetes, Docker, Prometheus, Grafana, TCP/IP, DNS, Scripting, Automation, Observability, Monitoring, Tracing, Networking 🏢 Description: ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are seeking a highly skilled Sr. Software Engineer to join our team in managing and enhancing reliability across a multi-data center environment. This role focuses on automating processes, building and implementing robust observability solutions, and ensuring seamless operations for mission-critical AI infrastructure. The ideal candidate will combine strong coding abilities with hands-on data center experience to build scalable reliability services, optimize system performance, and minimize downtime—including close partnership with facility operations to address physical infrastructure impacts. In an era where AI workloads demand near-zero downtime, this position plays a pivotal role in bridging software engineering principles with physical data center realities. By prioritizing automation and observability, team members in this role can reduce mean time to recovery (MTTR) by up to 50% through proactive monitoring and automated remediation. The primary objective of this team is to mitigate downtime and minimize impact to end-users from both scheduled and unscheduled maintenance, as well as events affecting onsite data centers. This is achieved through proactive automation, robust observability, and integrated software-physical reliability strategies. RESPONSIBILITIES: - Design, develop, and deploy scalable code and services (primarily in Python and Rust) to automate reliability workflows, including monitoring, alerting, incident response, and infrastructure provisioning. - Implement and maintain observability tools and practices, such as metrics collection, logging, tracing, and dashboards, to provide real-time insights into system health across multiple data centers. - Collaborate with cross-functional teams to identify reliability bottlenecks and automate solutions for fault tolerance, disaster recovery, capacity planning, and physical/environmental risk mitigation. - Troubleshoot and resolve complex issues in data center environments, including hardware failures, environmental anomalies, software bugs, and network-related problems, while adhering to reliability principles like error budgets and SLAs. - Optimize Linux-based systems for performance, security, and reliability, including kernel tuning, container orchestration, and scripting for automation. - Understand network topologies and concepts in large-scale, multi-data center environments to troubleshoot connectivity, routing, redundancy, and performance issues. - Participate in on-call rotations, post-incident reviews (blameless postmortems), and continuous improvement initiatives. - Mentor junior team members and document processes to foster a culture of automation and knowledge sharing. BASIC QUALIFICATIONS: - Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related technical field (or equivalent professional experience). - 3+ years of hands-on experience in site reliability engineering (SRE), infrastructure engineering, DevOps, or systems engineering in large-scale, distributed, or production environments. - Strong programming skills with proven production experience in Python; experience with Rust or another systems-level language (e.g., Go, C++) is essential. - Solid experience with Linux systems administration, performance tuning, kernel-level understanding, and scripting/automation in production environments. - Practical knowledge of containerization and orchestration technologies, such as Docker and Kubernetes. - Experience implementing observability solutions, including metrics, logging, tracing, monitoring tools, alerting, and dashboards. - Familiarity with troubleshooting complex issues in distributed systems, including software bugs, hardware failures, network problems, and environmental factors. - Understanding of networking fundamentals (TCP/IP, routing, redundancy, DNS) in large-scale or multi-site environments. - Experience participating in on-call rotations, incident response, post-incident reviews, and reliability practices such as error budgets or SLAs. - Ability to collaborate effectively with cross-functional teams. PREFERRED SKILLS AND EXPERIENCE: - 5+ years of experience in SRE or infrastructure roles in hyperscale, cloud, or AI/ML training environments with multi-data center setups. - Hands-on experience operating or scaling Kubernetes clusters at large scale, including automation for provisioning and high availability. - Proficiency in Rust for systems programming and performance-critical components. - Experience integrating software reliability tools with physical data center infrastructure (power, cooling, environmental monitoring). - Experience building automated remediation, fault tolerance, disaster recovery, capacity planning, or predictive failure detection systems. - Background in optimizing Linux-based systems for AI workloads, GPU clusters, or high-throughput compute environments. - Experience with bare-metal provisioning, data center interconnects, or hybrid/multi-site failover mechanisms. - Mentoring experience and strong documentation skills. xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

🏢 Summary: The role focuses on engineering production-grade AI features such as semantic search, intelligent assistants, and automated risk scoring by integrating external AI providers into a cybersecurity platform. You will own the full lifecycle from prototype to reliable, monitored production services, primarily using Python on Azure. This position emphasizes robust software engineering practices over model research or training. 🗂️ Requirements: 5+ years of professional experience building production systems in Python, Expert-level Python programming skills, Experience with ML frameworks and libraries, Proven experience shipping and operating production software, Experience integrating external APIs in production environments, Strong understanding of software architecture and design patterns, Practical experience with CI/CD pipelines, Experience with containerization using Docker, Understanding of AI/ML concepts including LLMs, embeddings, prompt engineering, RAG, Experience with unit and integration testing and mocking external services, Polish work permit, Professional proficiency in English 📃 Skills: Python, Azure, OpenAI, Anthropic, Docker, CI/CD, FastAPI, Flask, Pinecone, Weaviate, Chroma, .NET, REST, LLMs, RAG, Embeddings, Git 🏢 Description: About the Role As a Senior AI/ML Engineer you will be building AI-powered features at the core of our platform - semantic search, an intelligent assistant, automated risk scoring, and much more. We mainly integrate with external AI model providers (OpenAI, Anthropic, and others) to deliver these capabilities to our clients and internal users. This is a software engineering role, not a data science or ML research position. You won't train models from scratch or publish papers. You'll engineer production-grade systems that leverage AI to solve real cybersecurity problems. If you're a strong Python engineer excited about making AI reliable, maintainable, and impactful — we want to talk to you. We're looking for a versatile software engineer to own the journey from AI prototype to reliable production system: building robust integrations with external AI providers or fine-tuned models, standardizing our Python codebase and release pipelines, and ensuring our AI features meet the same quality bar as any other production service. What You'll Do Ship AI features end to end - from integration design through deployment to monitoring in production. You'll build and maintain Python services that power our AI-driven capabilities on Azure. Build production-ready AI / ML integrations - including retry logic, rate limiting, cost monitoring, fallback strategies, and abstraction layers that allow us to swap between model providers. Turn proofs of concept into reliable software - collaborate with our AI experts (who bring deep ML/data science expertise) to take working prototypes and engineer them into tested, documented, production-grade services. Standardize Python engineering practices - establish and evolve our code organization, testing strategies, CI/CD pipelines, and release processes for AI/ML features. Design clean service boundaries - our platform's core runs on .NET. You'll design and maintain well-defined APIs between the Python/AI layer and the rest of the system. Mentor and share knowledge - help other engineers grow their Python and AI engineering skills, and bring engineering rigor to the broader team's practices. Contribute to architecture decisions - work closely with other teams to shape how AI capabilities evolve within the platform. Who You Are Must-Haves 🔹 5+ years of professional experience building and maintaining production systems in Python. 🔹 Expert-level programming skills and proficiency with common ML frameworks and libraries. 🔹 A track record of shipping and operating software - not just building prototypes. You care about testing, monitoring, logging, and what happens after deployment. 🔹 Experience integrating external APIs in production systems - ideally AI/LLM provider APIs (OpenAI, Anthropic, Azure AI, or similar), but strong API integration experience in any domain counts. 🔹 Solid understanding of software architecture and design patterns - you have opinions about how to structure a Python project and can articulate trade-offs. 🔹 Practical knowledge of CI/CD pipelines, containerization (Docker), and modern development workflows. 🔹 A working understanding of AI/ML concepts - you know what embeddings, LLMs, prompt engineering, and RAG are. You can have a productive technical conversation with an ML specialist without needing every concept explained from scratch. 🔹 Experience with testing strategies - unit tests, integration tests, mocking external services. You instinctively write tests, not as an afterthought. 🔹 A highly adaptable, problem-solving and result-oriented mindset with the ability to work independently and take ownership in a fast-paced and dynamic environment. 🔹 Strong communication skills in English (our working language). 🔹 Willingness to learn continuously and share what you learn with the team. Nice-to-Haves 🔸 Experience with Azure cloud services. 🔸 Familiarity with FastAPI, Flask, or similar Python web frameworks. 🔸 Exposure to MLOps tooling or practices (model versioning, experiment tracking, feature stores). 🔸 Hands-on experience in Document AI / Intelligent Document Processing using traditional models and Generative AI. 🔸 Experience with vector databases (Pinecone, Weaviate, Chroma, or similar). 🔸 Any experience with .NET - helpful for cross-team collaboration, but not expected. 🔸 Background in or interest in cybersecurity as a domain. Your Team You'll join our Synapse team - a small, focused group responsible for all AI/ML capabilities within our platform. The team consists of: -> Team Leader / Architect - provides high-level architectural guidance, planning, and cross-stack delivery. -> AI / ML Engineer - deep expertise in AI/ML and data science. Your counterbalance: they bring the ML knowledge, you bring the production engineering discipline. -> AI / Backend Engineer - transitioning from .NET into AI engineering. A teammate you'll mentor and grow alongside. -> You - the person who bridges the gap between AI prototypes and reliable production systems. Why Join Us? / What We Offer: Competitive salary and benefits package. Remote work options and flexible working hours. Actual impact on the choice and shape of solutions developed. Opportunities for professional growth and development. Training and conference budget. A collaborative, innovative work environment with an iterative agile approach. The role is for six months with the possibility of extension. Both full-time and part-time cooperation are possible.

🏢 Summary: Full-time AI/ML Product Manager role responsible for defining and delivering AI/ML capabilities within a defense-focused software platform. The position owns the AI/ML roadmap, translates machine learning innovations into production features, and partners cross-functionally to integrate intelligent solutions into existing workflows. Requires strong AI/ML product experience, technical fluency, and ability to drive strategy in a fast-paced environment. 🗂️ Requirements: U.S. Citizenship, 5+ years of product management experience, 3+ years focused on AI/ML or data-driven products, Experience with ML development lifecycle, Experience launching AI/ML products in production, Bachelor's degree in business or technology-related field, Ability to travel up to 40% 📃 Skills: AI, ML, MachineLearning, DataScience, ModelTraining, ModelDeployment, ModelValidation, DataPreparation, ProductManagement, MarketResearch, CompetitiveAnalysis, PRD, UserStories 🏢 Description: Company Description Air is the leader in Enterprise Readiness. Our mission is to establish readiness as a real-time condition that is continuously achieved. Today, a dangerous Readiness Gap exists between what the front line needs and what is delivered. Our AI-native platform, Air Enterprise Readiness, aligns development, production, delivery, and sustainment into one coordinated execution system for government agencies and industrial suppliers. By revealing true capacity, exposing real constraints, coordinating resources, and executing at the speed of operational demands, the front line gets what it needs to succeed. Job Description We are seeking a customer-obsessed product manager to drive the development and integration of AI/ML capabilities within Air Enterprise Readiness platform. This is an individual contributor role responsible for defining, prioritizing, and delivering AI/ML solutions that enhance our Applications and transform how current and future users make critical decisions. As the AI/ML Product Manager, you will own the AI/ML roadmap and therefore be accountable for identifying opportunities where artificial intelligence and machine learning can deliver meaningful value to our customers, translating complex technical capabilities into user-friendly solutions, and ensuring the successful integration of our models and algorithms into Air Enterprise Readiness platform. You will need to think strategically about how to position Air as a leader in Defense AI, identify competitive advantages and market opportunities through AI/ML capabilities, and drive strategic decisions about how AI/ML innovations differentiate Air in the marketplace. You will partner with data scientists, ML engineers, application-aligned PMs, and our engagement teams to identify high-impact use cases, define requirements for ML-powered features, and ensure seamless delivery of intelligent capabilities that scale across our customer base. In this role, you will bridge the gap between cutting-edge AI/ML research and practical defense acquisition applications. In order to do this job well, you must possess a moderate technical understanding of AI/ML methodologies and emerging technology combined with exceptional product judgment to identify opportunities where AI/ML can deliver measurable customer value. You must work effectively cross-functionally in often ambiguous circumstances, translating complex technical capabilities into clear product requirements and articulating the value of AI/ML solutions both internally and externally to non-technical stakeholders. In a typical week, an AI/ML product manager could expect to: Spend time on site with users, seeking to understand their pain points and triangulate the commonalities where AI/ML can automate manual processes, enhance decision-making, or provide predictive insights Write detailed product requirements documents (PRDs) and user stories for AI/ML features Collaborate with data science and AI/ML engineering teams to assess the feasibility of proposed solutions Partner with designers and Application PMs to integrate AI/ML capabilities seamlessly into existing Air workflows, ensuring models enhance rather than disrupt user experiences Work with the sales team to articulate the value proposition of AI/ML features to prospective customers and understand market demand for intelligent automation Define success metrics for AI/ML initiatives Scope of Responsibilities Define and communicate the AI/ML product strategy and roadmap aligned with Air's positioning, mission, and customer needs Identify and prioritize high-impact opportunities where AI/ML can transform user workflows Validate concepts using the value proposition canvas/business model canvas, build a comprehensive business case, and communicate and defend the prioritization internally Conduct market research and competitive analysis to inform AI/ML product positioning Partner with data science, AI/ML, and software engineering teams to scope the expected associated investment costs/timelines, and ensure that the business can deliver on Facilitate market introduction of new features/functions while balancing tradeoffs of risk, cost, and speed Ensure smooth integration of prototyped features/functions into Air for utilization across customer accounts This is a full-time team member position, working in one of our offices at our Arlington, VA or Pittsburgh, PA locations. This role may require up to 40% travel Qualifications U.S. Citizenship is required Required Skills: 5+ years of product management experience with at least 3 years focused on AI/ML products or data-driven solutions Experience with ML development lifecycle, including data preparation, model training, validation, deployment, and monitoring Proven track record of successfully launching AI/ML products or features in production environments Strong value orientation, understanding of what matters for our customers, and why Self-starter, owner mentality Ability to thrive in a fast-paced, dynamic work environment Exceptional written and oral communication skills across all levels of the business Bachelor's degree in business or a technology-related field Desired Skills: Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship Experience in or exposure to the nuances of a startup or other entrepreneurial environment Experience in or around the DoW Full product lifecycle experience, from early idea through production and maintenance Familiarity with the value proposition canvas and/or business model canvas frameworks Advanced degree in a business or technical field We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we're eager to hear from you. We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we're eager to hear from you. Air is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.

🏢 Summary: Senior ML Infrastructure Engineer role focused on designing and optimizing high-speed copper and optical interconnects for large-scale AI training and inference clusters. The position involves end-to-end ownership of network fabric architecture, hardware validation, diagnostics, automation, and collaboration with vendors and ML teams. Candidates will work on cutting-edge AI networking technologies including photonics, SerDes, and next-generation optical systems. 🗂️ Requirements: 8+ years of experience with high-speed copper and optical interconnects, Master’s or PhD in Electrical Engineering, Photonics, or Physics, Expert knowledge of PAM4 SerDes, equalization, jitter, and crosstalk, Operational understanding of FEC, Retimers, TIAs, and Drivers, Experience with optical link budget analysis and diagnostics, Expertise in transceiver components and failure characterization, Knowledge of thermal, mechanical, power, and signal integrity constraints, Knowledge of SiPh design process, yield improvement, and reliability testing, Familiarity with CPO technologies and associated risks, Familiarity with supply chains, ODMs, and contract manufacturers, Strong problem-solving skills in fast-paced environments 📃 Skills: PAM4, SerDes, FEC, Retimers, TIAs, Drivers, SiPh, CPO, Photonics, IEEE, CMIS, DSP, VCSEL, microLED, THz, TDECQ, OMA, Python, Automation, Telemetry 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: xAI is building at a furious pace with the latest compute and switching hardware to help people understand the universe. We are looking for exceptional ML Infrastructure Engineers with deep expertise in high-speed interconnect technologies to design, build, and optimize the network fabric that powers large-scale AI training and inference clusters. This strategic role will drive innovation in high-bandwidth, low-latency, power-efficient interconnects critical for AI/ML clusters based on advanced computing platforms. You will have the opportunity to work on all modalities of interconnects connecting GPUs and switches both inside and between data centers, including our primary front and backend networks that train Grok and that customers use for inference. Engineers will own all aspects from design and development to build and operations. You will be expected to define and improve team processes and to contribute to scaling and maintenance efforts. You will focus on the physical layer and system-level integration of copper (ACC, AEC, CPC) and optical (FRO, LRO/TRO, LPO, AOC, CPO) interconnects that directly determine the performance, power efficiency, scale, and cost of next-generation AI/ML clusters. This is a highly technical, hands-on role bridging ML cluster requirements with cutting-edge interconnect hardware — ideal for engineers who love both large-scale AI systems and the physics/engineering of 200G+ SerDes, PAM4, photonics, signal integrity and diagnostics. RESPONSIBILITIES: - Design, validate, and productize high-speed copper and optical connectivity solutions for AI clusters (100k+ GPU scale). - Own vendor due diligence and onboarding for new 1.6T products including AEC and pluggable optical transceivers (DR4/8, FR4) including rigorous bring-up & characterization. - Investigate the opportunity for LPO and LRO in our network. - Evaluate early co-packaged and near-packaged engines for switches and GPUs. - Pathfinding for new interconnect modalities including VCSEL, microLED, THz radio-based solutions to improve network economics and reliability. - Work closely with vendors (transceiver, cable, SerDes, DSP, silicon photonics foundries) to influence roadmaps and ensure timely delivery of next-gen solutions. - Collaborate with ML training teams to translate workload communication patterns into concrete interconnect topology and optical reconfigurability requirements. - Perform system-level simulation of end-to-end fabric performance. - Drive failure analysis, root cause, and corrective actions for interconnect-related issues in production clusters through fleet-level metrics gathering and analysis. - Contribute to internal tooling and automation for interconnect health monitoring, telemetry, diagnostics, remediation and automated qualification pipelines. - Stay current with industry standards (OIF CMIS, IEEE) and emerging technologies (multi-core/hollow-core fiber, 448G SerDes, TFLN, ring resonators) BASIC QUALIFICATIONS: - At least 8+ years of hands-on experience in designing, deploying and operating high-speed copper and optical interconnects, preferably in a module design role or in a hyperscale datacenter environment. - Master's or PhD degree in Electrical Engineering, Photonics or Physics. - Deep knowledge of PAM4 SerDes performance, equalization, jitter, crosstalk. - Solid operational understanding of FEC, Retimers, TIAs and Drivers. - Deep knowledge of optical link budget analysis and performance metrics including TDECQ, OMA, Tcode, stressed receiver sensitivity and associated diagnostics. - Expertise in transceiver components including CW lasers, SiPh PICs, EML, DSP, passive subassemblies, their failure modes and characterization. - Knowledge of thermal, mechanical, power, signal integrity constraints in dense hardware. - Knowledge of SiPh design process, yield improvement and reliability testing. - Familiarity with CPO technologies and challenges/risk areas. - Familiarity with subcomponent supply chains and global manufacturers, ODMs and CMs. - Strong problem-solving skills and ability to thrive in a fast-paced, ambiguous setting. COMPENSATION AND BENEFITS: $180,000 - $440,000 USD Base salary is just one part of our total rewards package, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

🏢 Summary: Principal Engineer role focused on leading AI system architecture research and driving system-level design decisions for next-generation AI platforms. The position centers on modeling, evaluating, and optimizing compute, memory, and interconnect subsystems to improve performance, scalability, and efficiency of large-scale AI workloads. The role bridges AI workloads, hardware architecture, and quantitative system modeling to shape long-term AI infrastructure strategy. 🗂️ Requirements: PhD in Computer Science, Electrical Engineering, or related field, 15+ years of experience in system architecture for large-scale computing platforms, Hands-on experience with analytical and event-driven system-level performance modeling, Deep understanding of AI hardware architectures including compute, memory hierarchies, and interconnects, Strong knowledge of modern AI workloads such as LLMs and DLRMs, Experience translating workload analysis into architectural design decisions, Proficiency in Python, C++, and PyTorch, Ability to work onsite in San Jose 📃 Skills: Python, C++, PyTorch, AI, LLMs, DLRMs, Modeling, Simulation, Architecture, Hardware, Compute, Memory, Interconnects, Networking, Performance, Scalability, Power 🏢 Description: Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World's Technology Together Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities.Job Title: Principal Engineer, AI System Architect (Hardware) The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung's world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability. We are seeking a Principal AI System Architect who will play a Technical Lead role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung's long-term AI platform strategy. Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy Job ID: 42852 What You'll Do Technically Lead the architecture team with strong direction, shaping system‑architecture strategy and advancing key innovations Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems. Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale. Analyze representative and emerging system-level architectural research (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power. Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections. Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices. Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities. Communicate architectural insights and recommendations through clear technical presentations and documentation. Occasional domestic and international travel (<10%). What You Bring Ph.D. in Computer Science, Electrical Engineering, or a related field preferred, with 15+ years of experience in system architecture for large-scale computing platforms, with a strong focus on AI workloads Proven hands-on experience developing analytical and event-driven simulation models for system-level performance evaluation. Deep understanding of AI system hardware architectures, including compute, memory hierarchies, and high-performance interconnects. Strong knowledge of modern and emerging AI workloads, including LLMs, DLRMs, and large-scale training and inference systems. Demonstrated ability to translate workload characteristics and modeling results into actionable architectural design decisions. Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation. Excellent written, verbal, and presentation communication skills, with the ability to influence technical direction across teams. A collaborative mindset, intellectual curiosity, and resilience in tackling complex, open-ended system-level challenges. You're inclusive, adapting your style to the situation and diverse global norms of our people. You approach challenges with curiosity and resilience, seeking data to help build understanding. You're collaborative, building relationships, humbly offering support and openly welcoming approaches. Innovative and creative, you proactively explore new ideas and adapt quickly to change. #LI-SF1What We OfferThe pay range below is for all roles at this level across all US locations and functions. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. We also offer incentive opportunities that reward employees based on individual and company performance. This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours. Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community.Enjoy Time Away You'll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge.Care for Family Whatever family means to you, we want to support you along the way—including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies.Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you'll have support no matter where you are.Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Café and gym, plus virtual classes, make it easier.Embrace Flexibility Benefits are best when you have the space to use them. That's why we facilitate a flexible environment so you can find the right balance for you.Base Pay Range$219,000—$351,000 USDEqual Opportunity Employment Policy Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations. Recruiting Agency Policy We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings. Applicant AI Use Policy At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we prohibit the use of generative AI tools to misrepresent a candidate's true skills and qualifications. Permitted uses are limited to basic preparation, grammar, and research, but all submitted content and interview responses must reflect the candidate's genuine abilities and experience. Violation of this policy may result in immediate disqualification from the hiring process. Applicant Privacy Policyhttps://semiconductor.samsung.com/about-us/careers/us/privacy/

🏢 Summary: Senior Engineer role on the Reliability Command Center team focused on leading incident response, improving operational excellence, and building reliability and observability tooling at scale. The position drives company-wide incident management strategy, monitoring frameworks, and failure mitigation across distributed systems. This role emphasizes incident leadership, reliability engineering, and cross-functional coordination to reduce customer impact. 🗂️ Requirements: 5+ years software engineering experience, 2+ years in reliability engineering, infrastructure, distributed systems, or production operations, Experience operating production systems, Incident leadership experience (IMOC, incident commander, oncall), Knowledge of systems reliability and fault-tolerant architecture, Experience with multi-region or multi-cluster architectures, Experience with capacity planning and failover strategies, Experience with observability and monitoring frameworks, Ability to improve MTTD and MTTR metrics 📃 Skills: OpenTelemetry, Prometheus, Grafana, DistributedSystems, Observability, Monitoring, Alerting, IncidentManagement, Infrastructure, Reliability, MTTD, MTTR, Failover, CapacityPlanning 🏢 Description: Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.About the team & role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Robinhood Command Center (RCC) is a newly formed reliability team that serves as the front line for detecting, coordinating, and mitigating production incidents across Robinhood. As part of Robinhood’s broader reliability initiative, RCC works closely with product engineering, reliability, observability, infrastructure, and business teams to reduce customer impact and shorten incident duration. As a Senior Engineer, you will be part of the founding RCC team, helping define how Robinhood responds to and learns from incidents at scale. This is a highly visible role focused on incident leadership, operational excellence, and reliability tooling. You will not own product services or core infrastructure, but you will own the processes and tools that enable fast, high-quality incident response. This role is based in our Menlo Park, Califronia office, with in-person attendance expected at least 3 days per week. What you'll do: Serve as a senior technical leader driving the long-term reliability and observability strategy across Robinhood’s infrastructure Partner closely across many different types of engineers to raise the bar for operational excellence and incident response Lead incident mitigation efforts by coordinating service owners, facilitating time-sensitive decisions like rollbacks, traffic shifts, and maintaining a clear source of truth during active incidents Develop and maintain incident management processes and procedures to ensure timely resolution and minimize customer impact Own incident discovery at the company level by defining and maintaining global dashboards and alerts tied to critical user journeys (CUJs), availability, and business-impact metrics Own and evolve incident response tooling and processes, including education, adoption, and measurement of MTTD/MTTR improvements Drive post-incident governance and learning, defining standards for postmortems, SEV reviews, and follow-up tracking to ensure durable reliability improvements Design and implement next-generation failure mitigation strategies that avoid full-region or full-datacenter failovers Define and build frameworks to improve monitoring, alerting, and observability across hundreds of services and systems Define and own the roadmap of bringing observability to critical user journeys for Robinhood’s products Deliver key insights and executive-level reporting to enable better business decisions around service quality and reliability Act as a force multiplier through mentoring, technical influence, and contributions to hiring and engineering culture What you bring: 5+ years of software engineering experience, including significant experience operating production systems 2+ years focused on reliability engineering, infrastructure, distributed systems, or production operations Hands-on experience serving in incident leadership roles (e.g., IMOC, incident commander, primary oncall) Strong communication and cross-functional collaboration skills, especially during high-severity incidents Deep knowledge of systems reliability, observability frameworks, and fault-tolerant architecture design Experience with multi-region or multi-cluster architectures, capacity planning, and failover strategies Familiarity with modern observability stacks (e.g., OpenTelemetry, Prometheus, Grafana) Demonstrated ability to drive measurable improvements in MTTD, MTTR, availability, or customer impact What we offer: Challenging, high-impact work to grow your career Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more Employer-paid life & disability insurance, fertility benefits, and mental health benefits Time off to recharge including company holidays, paid time off, sick time, parental leave, and more! Exceptional office experience with catered meals, events, and comfortable workspaces In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits. Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process. Base Pay Range:Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$196,000—$230,000 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$172,000—$202,000 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$153,000—$179,000 USDClick here to learn more about our Total Rewards, which vary by region and entity. If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application. Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

🏢 Summary: Senior Staff DevOps & Site Reliability Engineer role focused on designing, automating, and operating scalable, secure hybrid and multi-cloud infrastructure across Azure, AWS, and on-prem environments. The position drives SRE practices, AIOps integration, and AI-enabled automation to ensure high availability, compliance, and performance in a regulated healthcare environment. This is a hands-on strategic role influencing infrastructure architecture, reliability standards, and modernization initiatives. 🗂️ Requirements: Bachelor's degree in Information Systems, Computer Science, Engineering, or related field, 8–10 years experience in Infrastructure Engineering, DevOps, or SRE, Hands-on experience with Azure and AWS in production environments, Experience designing and operating hybrid cloud and on-prem infrastructure, Expertise in Infrastructure as Code using Terraform or Bicep, Strong knowledge of SRE practices (SLIs, SLOs, incident management), Experience with Active Directory, Hybrid AD, Entra ID, and Group Policy, Experience implementing zero trust and secure access architectures, Experience with AIOps, predictive analytics, and automated remediation, Knowledge of HIPAA, SOC2 Type II, or HITRUST compliance, Experience with secure remote infrastructure access (VDI, bastion hosts, privileged access workstations) 📃 Skills: Azure, AWS, Terraform, Bicep, AIOps, SRE, ActiveDirectory, EntraID, GroupPolicy, ZeroTrust, VDI, HIPAA, SOC2, HITRUST, VPN, HybridCloud, OnPrem, Observability, Automation, DevOps 🏢 Description: Empower Pharmacy is a visionary healthcare company dedicated to making quality, affordable medication accessible to millions of patients nationwide. As the most advanced 503A compounding pharmacy and FDA-registered 503B outsourcing facility serving the functional medicine markets, we are proud to be recognized as one of Houston's fastest-growing private companies and ranked #116 in Healthcare & Medical on the Inc. 5000 List for 2025. Our strength lies in four core values—People, Quality, Service, and Innovation. Guided by these principles, we deliver a uniquely integrated approach to healthcare through vertical supply chain integration, advanced technology, and a relentless pursuit of excellence. From manufacturing to distribution to quality control, our teams work collaboratively to push boundaries, improve patient outcomes, and redefine medication accessibility. At Empower, joining our team means more than starting a new job, it means becoming part of a mission to transform healthcare. We empower our employees to innovate, grow, and make a meaningful impact every day. Here, your ideas are valued, your growth is supported, and your contributions are celebrated. If you thrive in a fast-paced, transformative environment where innovation meets purpose, Empower Pharmacy is the place for you. Let's revolutionize healthcare together.Position Summary: The Staff DevOps & Site Reliability Engineer drives enterprise infrastructure reliability, scalability, and security across hybrid and multi-cloud environments, directly impacting system uptime, product quality, and operational efficiency. This role owns architecture, automation, and SRE practices spanning Azure, AWS, and on-prem platforms, ensuring resilient, compliant systems in Empower's highly regulated 503A/503B environment. Leveraging AI as a force multiplier, the role accelerates deployment speed, enhances observability, improves decision-making, and enables predictive operations at scale. As a senior individual contributor, this position influences infrastructure strategy, standards, and modernization initiatives while maintaining hands-on execution rigor. Success requires exceptional strategic thinking, deep technical expertise, and continuous learning agility to drive innovation, optimize performance, and uphold reliability in a hyper-growth, compliance-driven organization. Responsibilities: Infrastructure Engineering Cloud Architecture: Design and operate scalable hybrid and multi-cloud infrastructure across Azure, AWS, and on-prem environments, ensuring high availability, resilience, and cost efficiency while leveraging AI-driven insights to optimize system performance, resource allocation, and architectural decisions. Platform Automation: Build and maintain Infrastructure as Code frameworks using Terraform, Bicep, or similar tools, enabling consistent, auditable deployments while integrating AI-assisted automation to accelerate provisioning, reduce errors, and enhance infrastructure lifecycle management. Network Design: Engineer secure, high-performance networking solutions including hybrid connectivity, segmentation, VPNs, and zero trust architectures, using AI-enhanced analytics to proactively detect vulnerabilities, optimize traffic flows, and ensure secure, compliant communication. Site Reliability Engineering Reliability Engineering: Establish and evolve SRE practices including SLIs, SLOs, and error budgets, leveraging AI-driven observability platforms to improve system reliability, automate incident detection, and enable proactive remediation. Incident Management: Lead incident response, root cause analysis, and post-incident improvements, applying AI-powered anomaly detection and predictive analytics to reduce mean time to resolution, prevent recurrence, and strengthen operational resilience. Capacity Planning: Drive intelligent capacity forecasting and performance optimization using AI models, ensuring infrastructure scales efficiently with demand while maintaining cost discipline, system reliability, and alignment with business growth objectives. AI and Automation Enablement AIOps Integration: Design and implement AI-driven operational capabilities, including predictive monitoring, anomaly detection, and automated remediation, transforming traditional operations into intelligent, self-healing systems. Data Infrastructure: Build AI-ready infrastructure platforms that support advanced analytics, automation pipelines, and enterprise AI workloads, ensuring secure, scalable environments that enable innovation while maintaining regulatory compliance. Decision Intelligence: Leverage AI and data-driven insights to inform infrastructure strategy, optimize performance, and enhance operational decision-making. Knowledge and Skills: Deep expertise in Azure and AWS architecture, hybrid cloud design, and infrastructure automation using Terraform, Bicep, or similar tools. Strong proficiency in Site Reliability Engineering practices, including observability, incident management, and AI-driven monitoring and automation platforms. Advanced knowledge of identity systems including Active Directory and Entra ID, with experience implementing secure access controls and zero trust architectures. Experience with AIOps, including predictive analytics, anomaly detection, capacity forecasting, and automated remediation within infrastructure and DevOps ecosystems. Experience and Qualifications: Bachelor's degree in Information Systems, Computer Science, Engineering, or related field required; master's degree preferred. 8–10 years of hands-on experience in infrastructure engineering, DevOps, or Site Reliability Engineering roles. Proven experience designing, implementing, and operating hybrid infrastructure solutions across on-premises and cloud environments. Hands-on experience designing and operating solutions across both Microsoft Azure and AWS in production environments. Strong hands-on expertise in Microsoft Active Directory, Hybrid AD, Microsoft Entra ID, and Group Policy. Experience working in regulated environments with knowledge of HIPAA, SOC 2 Type II, and/or HITRUST compliance requirements. Experience operating infrastructure remotely using secure access methods, including VDI, bastion hosts, or privileged access workstations. Strong problem-solving, documentation, and communication skills, with the ability to influence technical direction and drive engineering best practices across teams. Preferred certifications include Azure Solutions Architect Expert, AWS Solutions Architect, Azure Administrator, AWS SysOps Administrator, Azure DevOps Engineer Expert, AWS DevOps Engineer Professional, HashiCorp Terraform Associate, CISSP, CISM, Microsoft Identity and Access Administrator, or Azure Security Engineer. Key Competencies: Customer Focus: Builds trust through customer-centric solutions. Strategic AI: Guides responsible AI adoption and adaptation. Optimizes Work Processes: Drives efficiency with continuous improvement. Collaborates: Partners effectively to achieve shared goals. Resourcefulness: Secures and deploys resources efficiently. Manages Complexity: Simplifies and solves complex challenges. Ensures Accountability: Delivers on commitments with integrity. Situational Adaptability: Adjusts approach to shifting conditions. Communicates Effectively: Tailors messages to diverse audiences. Values: People: Empowering people defines who we are. Quality: Excellence in every product, every time. Service: Serving others is our highest purpose. Innovation: Advancing care through technology and discovery. Employee Benefits, Health and Wellness: We offer comprehensive benefits to support your health, well-being, and future, including medical, dental, and vision coverage, paid time off, 401(k) matching, wellness perks, IV therapy, and compounded medications. Learn more: https://careers.empowerpharmacy.com/benefits/ Physical Requirements: While performing the responsibilities of the job, the employee is required to talk and hear. The employee is often required to remain in a stationary position for a significant amount of the workday and frequently use their hands and fingers to handle or feel in order to access, input, and retrieve information from the computer and other office productivity devices. Employees are regularly required to move about the office and around the corporate campus. The employee is regularly required to stand, walk, reach with arms and hands, climb or balance, and to stoop, kneel, crouch or crawl.

🏢 Summary: Remote AI Lead DevOps Engineer role responsible for defining and executing the MLOps and CI/CD strategy for enterprise AI platforms. The position focuses on architecting secure, compliant, and fully automated ML lifecycle governance, ensuring auditability, reproducibility, and large-scale reliability. The role combines technical leadership with hands-on design of cloud-native, DevSecOps-driven AI infrastructure. 🗂️ Requirements: 8–10 years DevOps or Cloud Engineering experience, Minimum 3 years in technical leadership or architect role, Strong knowledge of end-to-end ML lifecycle, Expertise in CI/CD pipeline design and implementation, Advanced Infrastructure as Code experience, Experience with SAST and DAST implementation, Strong IAM and access control management in cloud, Ability to design observability frameworks for ML systems, Experience with configuration management in multi-cloud environments, Knowledge of database scaling and security, Experience implementing model governance and auditability practices 📃 Skills: MLOps, CI/CD, DevSecOps, Azure, AzureDevOps, GitHubActions, Jenkins, Terraform, CloudFormation, SAST, DAST, IAM, Ansible, Puppet, MySQL, PostgreSQL, MongoDB, Observability, Git 🏢 Description: This is a remote position. We are looking for an AI Lead DevOps Engineer to spearhead the MLOps strategy for our high-impact AI accounts. With 8–10 years of experience, you will provide the technical leadership necessary to design robust, compliant, and highly automated AI platforms. You aren't just managing pipelines; you are architect the entire lifecycle governance—ensuring reproducibility, audibility, and security at an enterprise scale. Key Responsibilities: Strategic Leadership: Provide technical direction for the DevOps squad, defining the CI/CD and MLOps roadmap for the account. Model Governance & Evaluation: Implement automated model evaluation pipelines to track accuracy, precision, and recall metrics in production. Enterprise Security: Lead the DevSecOps strategy, ensuring all AI deployments comply with enterprise security standards and global data regulations. Platform Enablement: Architect self-service platforms that allow ML engineers to deploy models with minimal friction while maintaining strict governance guardrails. Auditability & Reproducibility: Ensure that every ML experiment is fully auditable through sophisticated pipeline and dataset versioning strategies. Mentorship: Mentor senior and junior engineers, driving best practices in automation, IaC, and cloud-native architecture. Requirements 8–10 years of experience in DevOps/Cloud Engineering, with at least 3 years in a technical leadership or architect-level role. Deep understanding of the end-to-end ML lifecycle (training, validation, deployment, and retraining loops). Mastery across Azure DevOps, GitHub Actions, and Jenkins. Expert-level Terraform or CloudFormation skills, including modular architecture and cross-account cloud deployments. Significant experience implementing SAST/DAST tools and managing complex IAM/Access Control frameworks in a cloud environment. Ability to design custom observability frameworks that track model drift, pipeline failures, and infrastructure ROI. Advanced knowledge of configuration management tools like Ansible or Puppet for complex multi-cloud environments. Solid understanding of database scaling and security for MySQL, PostgreSQL, and MongoDB. Understanding of how DevOps practices support responsible AI (e.g., bias tracking and audit logs). Exceptional ability to collaborate with Architects and Data Scientists to translate high-level AI needs into operational reality. Native or C1-level English, with the ability to present technical strategies to senior stakeholders. Benefits Professional training programs Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row

🏢 Summary: Lead the vision and delivery of AI-powered infrastructure remediation capabilities that proactively detect and autonomously resolve issues across cloud environments. Own the end-to-end product roadmap spanning UI, CLI, agents, and developer workflows, ensuring safe, trustworthy automation. Drive cross-functional execution to build AI systems that identify, execute, and validate fixes across distributed systems. 🗂️ Requirements: 5+ years Product Management experience in cloud infrastructure or SaaS, Experience shipping AI-driven products, Knowledge of large language models and agent-based systems, Understanding of AI evaluation and safety concepts, Technical knowledge of cloud infrastructure, Ability to reason about APIs and distributed systems, Experience building products for developer or operator audiences 📃 Skills: AI, LLM, Agents, Cloud, SaaS, APIs, DistributedSystems, Infrastructure, Observability, Automation, CLI, UI 🏢 Description: As a Senior Product Manager – AI Remediation, you will define, build, and launch capabilities that proactively and autonomously resolve issues before they escalate into production incidents. You will own a broad roadmap focused on AI-powered automation across infrastructure types including hosts, containers, serverless, and networking. This role spans multiple developer entry points, from the Datadog application to IDEs, CLI, and other workflows, ensuring a consistent experience wherever users operate. You’ll partner closely with Engineering, Design, and customers to build AI systems and agents that safely identify, execute, and validate fixes while preserving trust. This is an opportunity to lead a high-impact initiative at the intersection of AI, infrastructure operations, and autonomous observability. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the product vision and roadmap for AI-driven infrastructure remediation, evolving Datadog from passive observability to proactive, safe action. Define and launch an end-to-end remediation experience across the Datadog UI, agent and chat interfaces, CLI, and other developer workflows. Partner with Design to create user-facing experiences that make proactive remediation intuitive, transparent, and trustworthy. Define AI-powered building blocks that identify remediation opportunities and safely execute actions while maintaining customer confidence. Collaborate cross-functionally with infrastructure monitoring, core platform, and AI product teams to integrate remediation capabilities across the Datadog platform. Establish quality standards and success metrics for remediation, including correctness, safety, and user trust. Who You Are: 5+ years of Product Management experience shipping technical products in cloud infrastructure or SaaS environments, ideally for developer or operator audiences. Have experience shipping AI-driven products and comfortable reasoning about large language models, agent-based systems, evaluation, and safety considerations. Customer-focused, with empathy for how developers and operators work across applications, terminals, and collaboration tools. Technically fluent, with knowledge of cloud infrastructure and the ability to reason about APIs, distributed systems, and AI/ML concepts. Comfortable making thoughtful decisions in ambiguous environments and balancing speed with long-term platform integrity. Clear and concise communicator who can lead cross-functional initiatives and align stakeholders around a shared vision. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Generous and competitive benefits package New hire stock equity (RSUs) and employee stock purchase plan Continuous career development and pathing opportunities Employee-focused best in class onboarding Internal mentor and cross-departmental buddy program Friendly and inclusive workplace culture Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$187,000—$240,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.