System Software Engineer, Networking

🏢 Summary: Opportunity for a Forward Deployed Engineer (GTM) to lead the technical side of enterprise AI platform deals, owning discovery, architecture design, and proof-of-concept delivery for production-grade agentic AI systems. The role combines backend engineering, AI/ML expertise, and customer-facing technical leadership to drive successful adoption of an AI control plane and Kubernetes-based compute platform. You will shape production AI architectures, build integrations and workflows, and influence product direction based on field feedback. 🗂️ Requirements: 3–7 years of backend software engineering experience, Production systems ownership and delivery experience, Proficiency in Python, Go, or TypeScript, Experience with Kubernetes or major cloud platforms (AWS, Azure, or GCP), Hands-on experience with LLMs, agents, evals, or ML pipelines in production, Ability to lead architecture discussions with engineering stakeholders 📃 Skills: Python, Go, TypeScript, Kubernetes, AWS, Azure, GCP, LLM, LangChain, vLLM, SGLang, Triton, MCP, ML, MLOps 🏢 Description: About TrueFoundry Every production AI system whether it's powering customer support, writing code, analyzing financial data, or diagnosing medical conditions needs the same foundational infrastructure. A way to route between models. A way to manage tools and integrate them securely. A way to orchestrate agents and enforce governance. A unified compute layer to run it all. That infrastructure layer is being built right now. We're TrueFoundry, and we're building it. We're looking for a Forward Deployed Engineer- GTM to join the team. The Problem We're Solving Companies are moving beyond simple chatbots to production agentic systems. These systems route between OpenAI, Anthropic, Google, and self-hosted models. They integrate dozens of tools via protocols like MCP. They orchestrate multi-agent workflows where agents coordinate with other agents. The infrastructure to support this doesn't exist yet. You can't just duct-tape together a few API calls and call it production-ready. You need a control plane that handles: - Intelligent routing with observability, cost policies, and fallback logic - Centralized tool and MCP server management with security and lifecycle controls - Agent orchestration with governance and guardrails - A unified compute layer to run self-hosted models, custom tools, and agents We've built two products to solve this: AI Gateway is the control plane five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance. AI Deploy is the compute layer of Kubernetes-based platform that abstracts ML workloads as standard software primitives, so everything runs on unified infrastructure. We're Series A, backed by Intel Capital and Sequoia. Companies like CVS, Mastercard, Siemens, Paytm, Synopsys, and Zscaler run production AI workloads on our platform. What you'll do - Own the technical arc of the deal: discovery and the in-depth demo, the architecture discussion with the customer's engineering leaders, and the POC - all the way through to close. - Win the POC on technical merit: Co-define the success criteria with the customer, run the execution tracker and the milestones, and write the integration glue, agent workflows, and eval pipelines that prove value in their environment. The goal is delivered impact, not lines of code. - Make the architecture calls that decide how the customer would run AI in production. You are the technical decision-maker in the room - the CTO in the room - and the person their engineering leaders trust. - Be the technical face of TrueFoundry to enterprise customers, and earn the credibility that turns an evaluation into a signed contract. - Steer the product. You see, first-hand, what customers pull toward and where their first production win lands. Compile that field signal and bring structured, data-backed asks to TrueFoundry's engineering and product teams - your intuition helps shape the roadmap. Who we're looking for - Backend Engineering Experience: 3 to 7 years of backend software engineering experience with production systems you have shipped and owned. Strong in Python, Go, or TypeScript. Comfortable with Kubernetes or any major cloud (AWS, Azure, GCP). - Business Acumen: You don't just question the how but also the why - discovering impact, architecture design and deal-winning opportunities. - AI and ML literacy: You have worked with LLMs, agents, evals, or ML pipelines in production. Familiarity with the modern stack (vLLM, SGLang, LangChain, Triton, model serving) is a strong plus. - Design and Architecture: Comfortable leading an architecture discussion with a customer's engineering leaders, then doing the work yourself. High agency and a bias for action. We especially welcome founding engineers and CTOs of early-stage startups, as well as engineers from infrastructure, MLOps, and developer-tool companies. Growth path Engineering ladder: Senior FDSE to Staff or Principal FDSE, with named-account ownership and architectural authority at every level. Leadership ladder: Lead FDSE to Head of FDSE, building and running the function. Cross-functional: the role builds the breadth that leads to CTO, VP of Engineering, and founder paths. Many FDSE alumni have gone on to start their own companies.

🏢 Summary: The role focuses on designing and building a high-performance Software-Defined Networking (SDN) platform for AI and research workloads, enabling scalable, isolated, and automated networking using DPU-accelerated infrastructure. You will develop orchestration, provisioning, and lifecycle management systems integrating Kubernetes, SLURM, and GPU clusters. The position emphasizes programmable networking, multi-tenancy, and low-latency connectivity for distributed computing environments. 🗂️ Requirements: 5+ years of software engineering experience in network platforms or SDN systems, Strong knowledge of Kubernetes networking architecture and CNI plugins, Deep understanding of TCP/IP, VLANs, VXLAN, BGP, OSPF, and data center networking, Proven experience with SDN concepts and network virtualization, Proficiency in Go and Python, Strong experience with Linux networking stack and Open vSwitch, Familiarity with DPU or SmartNIC architectures and SR-IOV, Understanding of RDMA, RoCE, InfiniBand, and low-latency networking, Experience designing scalable network orchestration or automation systems 📃 Skills: Go, Python, Kubernetes, CNI, TCP/IP, VLAN, VXLAN, BGP, OSPF, SDN, Linux, OpenvSwitch, SR-IOV, Bluefield, RDMA, RoCE, InfiniBand, Terraform, FastAPI, gRPC 🏢 Description: Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads. We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance. Your Role: You will be foundational to building our software-defined networking (SDN) platform that enables high-performance, isolated networking for distributed computing, model training, inference, and data-intensive workloads. Working closely with our network, infrastructure, and product teams, you'll design and implement the network orchestration and provisioning systems that manage DPU-accelerated networking, tenant isolation, and network lifecycle management – enabling researchers and engineers to access enterprise-grade networking with cloud-like simplicity. Job Responsibilities: Software-Defined Networking Architecture: Collaborate with infrastructure to design and build scalable SDN orchestration systems leveraging NVIDIA Bluefield-3 DPUs to deliver programmable, high-performance networking for AI workloads with hardware-accelerated forwarding isolation. Research Cluster Networking: Design and implement networking systems for research computing environments including Kubernetes and SLURM clusters, enabling high-performance connectivity, optimized network topology for distributed workloads, and seamless integration with cluster orchestration systems. Network Provisioning & Lifecycle Management: Implement automated SDN provisioning systems that handle VPC creation, subnet allocation, routing configuration, and network resource lifecycle from deployment through decommissioning. DPU Platform Engineering: Develop platform capabilities for managing Bluefield-3 DPUs including SR-IOV virtual function management, OVS offload configuration, network function deployment, and integration with compute orchestration systems. Multi-Tenancy & Network Isolation: Build enterprise-grade network isolation using VPCs, VXLAN, and hardware-accelerated forwarding to ensure complete tenant separation while maintaining high-performance connectivity for GPU clusters and distributed workloads. High-Performance Networking: Collaborate with infrastructure to optimize network paths for RDMA, RoCE, and GPU-to-GPU communication, ensuring minimal latency and maximum throughput for distributed training and large-scale computational workloads. Network APIs & Integration: Develop robust APIs and SDKs for network resource management that integrate seamlessly with compute and storage platforms, enabling programmatic network provisioning and configuration. Network Observability: Implement comprehensive network monitoring, telemetry, and troubleshooting systems that provide visibility into network performance, utilization, and tenant traffic patterns.Security & Policy Management: Build platform network security features including security groups, firewall rules, and policy enforcement that protect tenant workloads while enabling flexible network configuration. Requirements: Experience: 5+ years in software engineering with proven experience building network platforms, SDN systems, or network automation for production environments. Kubernetes Networking & Container Orchestration: Strong familiarity with Kubernetes networking architecture, CNI plugins, service networking, and network policies. Understanding of pod networking, services, ingress, and how Kubernetes manages network resources. Networking Expertise: Deep understanding of networking fundamentals including TCP/IP, VLANs, VXLAN, BGP, OSPF, routing protocols, and data center network architectures.Software-Defined Networking: Background in SDN concepts, network virtualization, overlay networks, and programmable networking technologies. Programming Skills: Experience with Go and Python for performance-critical networking components and services is highly valued. Linux Networking: Strong experience with Linux networking stack, including network namespaces, iptables/nftables, Open vSwitch, and kernel networking systems. DPU & SmartNIC Experience: Familiarity with DPU/SmartNIC architectures (Bluefield, or similar), SR-IOV, hardware offload capabilities, and programmable networking hardware – or strong ability to learn quickly. High-Performance Networking: Understanding of RDMA, RoCE, Infiniband, and low-latency networking requirements for distributed computing and GPU workloads. Problem-Solving & Architecture: Demonstrated ability to solve complex networking performance and scalability challenges while balancing pragmatic shipping with good long-term architecture. Autonomy & Communication: Comfortable navigating ambiguity, defining requirements collaboratively, and communicating technical decisions through clear documentation. Commitment to Growth: Growth mindset with continuous focus on learning and professional development. Preferred Qualifications Background provisioning or managing networking for research computing environments (Kubernetes, SLURM, or HPC clusters) Experience with NVIDIA Bluefield DPU programming and DOCA framework Background with network function virtualization (NFV) and service function chaining Knowledge of Kubernetes networking (CNI plugins, network policies, service mesh) Experience building network control planes or SDN controllers Familiarity with network automation frameworks and infrastructure-as-code for networking Understanding of data center fabric architectures (spine-leaf, CLOS topologies) Experience with network security and compliance requirements in regulated industries Background building networking for research institutions, HPC environments, or cloud providers Key Technologies Go, Python, NVIDIA Bluefield DPUs, Open vSwitch, VXLAN, SR-IOV, RDMA, RoCE, InfiniBand, BGP, Linux networking, Terraform, FastAPI, gRPC Why Moonlite Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure. Hands-On Ownership: As an early engineer, you'll have end-to-end ownership of projects and the autonomy to influence our product and technology direction. Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments. Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving. Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space. We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together. #li-remote

🏢 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: Senior Software Engineer role focused on improving reliability and automation across multi-data center AI infrastructure. The position combines strong software engineering skills with hands-on data center and systems expertise to build observability, automate remediation, and minimize downtime in mission-critical environments. The engineer will design scalable services, optimize Linux systems, and support distributed infrastructure with near-zero downtime requirements. 🗂️ 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 distributed production environments, Strong programming experience in Python, Solid Linux systems administration and performance tuning experience, Experience with Docker and Kubernetes or similar orchestration tools, Experience implementing observability solutions (metrics, logging, tracing, monitoring, alerting), Knowledge of networking fundamentals (TCP/IP, routing, DNS, redundancy), Experience troubleshooting distributed systems including hardware and network issues, Experience with on-call rotations and incident response practices, Ability to collaborate with cross-functional technical teams 📃 Skills: Python, Rust, Linux, Docker, Kubernetes, Prometheus, Grafana, TCP/IP, DNS, C++, Go 🏢 Description: 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, based on industry benchmarks from high-scale environments like those at hyperscale cloud providers. 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, ensuring our AI infrastructure remains resilient, scalable, and at the cutting edge of innovation. RESPONSIBILITIES: - Design, develop, and deploy scalable code and services (primarily in Python and Rust, with flexibility for emerging languages) 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—including software development, network engineering, site operations, and facility operations—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 (e.g., Kubernetes), 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 to enhance overall site reliability. - 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 strong fundamentals in a systems-level language (e.g., Go, C++). - 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 (or similar systems). - Experience implementing observability solutions, including metrics, logging, tracing, monitoring tools (e.g., Prometheus, Grafana), 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 (blameless postmortems), and reliability practices such as error budgets or SLAs. - Ability to collaborate effectively with cross-functional technical teams. PREFERRED SKILLS AND EXPERIENCE: - 5+ years of experience in SRE or infrastructure roles in hyperscale, cloud, or AI/ML training infrastructure environments. - Hands-on experience operating or scaling Kubernetes clusters at large scale. - 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.

🏢 Summary: The offer is for a DevOps Engineer responsible for maintaining and developing production infrastructure for a large-scale, real-time, multi-tenant AI and big data platform. The role focuses on ensuring reliability, scalability, and automation of cloud-based systems while collaborating closely with backend engineers. It involves designing infrastructure solutions, improving CI/CD processes, and supporting high-traffic, data-intensive environments. 🗂️ Requirements: Experience with production systems in cloud environments (Azure preferred), Good knowledge of Linux systems, Understanding of basic networking concepts, Experience with CI/CD pipelines, Experience with Infrastructure as Code tools, Hands-on experience with Kubernetes or container platforms, Experience with automation of deployments and infrastructure provisioning, Experience with incident handling and root cause analysis, Hands-on use of AI coding tools in software engineering work 📃 Skills: Azure, Linux, Networking, CI/CD, IaC, Kubernetes, Containers, Kafka, Databases, Monitoring, Observability, Security, AI, Claude, Cursor, Copilot 🏢 Description: We successfully deliver an all-in-one tool - Synerise (YouTube link) . An ever-evolving behavioral data platform, enhanced by AI to generate outstanding ROI in more than 30 markets for industry leaders in Retail, Banking, eCommerce, Automotive, Insurance, and Telco, processing more than 150 billion transactions annually. However, we don't limit ourselves solely to this solution. We're building BaseModel (website link) - a foundation model for behavioral data embedded within a novel platform for enterprise Data Science teams, that is another step on our path to create innovation in AI and demonstrate its potential for the business world. ‍ Having such great solutions, we are looking for a highly motivated DevOps Engineer  to join our brave and brilliant Synerise Team. See if you fit our diverse and dynamic environment, where we constantly evolve together with the growth of our clients. ‍ What will you do on a daily basis? Maintain and develop production infrastructure for a large-scale, real-time multi-tenant platform. Work closely with backend engineers to support reliability, scalability, and availability of services. Implement and improve automation for deployments, infrastructure provisioning, and operational tasks. Participate in incident handling, root cause analysis, and post-incident improvements. Take responsibility of designing new infrastructure solutions and initiatives. What will make us a perfect match? Experience working with production systems in cloud environments (Azure preferred). Good understanding of Linux systems and basic networking concepts. Familiarity with CI/CD pipelines and Infrastructure as Code tools. Hands-on experience with Kubernetes or container-based platforms. Willingness to take responsibility for the quality and stability of systems you work on. Practical, problem-solving mindset and openness to learning new technologies. Hands-on experience using AI coding (e.g., Claude Code, Cursor, GitHub Copilot) as part of daily software engineering work. What will convince us even more? Exposure to data-heavy or event-driven systems (e.g. Kafka, multi-terabyte databases). Basic knowledge of monitoring, alerting, and observability practices and tooling. Interest in system performance, reliability, or cloud cost efficiency. Awareness of security considerations in cloud and infrastructure environments. Exposure to infrastructure handling large traffic volumes and data throughput. What can we provide for you? Work on a production-grade product used by enterprise customers in the AI and big data domain. Opportunity to grow technically while working with real-world, distributed systems at scale. Support from experienced engineers and space to take on more responsibility over time. Influence on day-to-day technical decisions within your team. Fully remote work model.

🏢 Summary: The role focuses on designing and building scalable data integration and connector applications that replicate and process data from diverse external systems into a cloud-based data platform. It involves developing APIs, frameworks, and infrastructure to standardize connector development, optimize ingestion performance, and ensure secure data transfer in distributed cloud environments. The position also includes technical leadership, collaboration with stakeholders, and mentoring engineers. 🗂️ Requirements: 5+ years experience designing and supporting large-scale systems, Experience building high-performance scalable software in distributed cloud environments, Strong proficiency in Java, Experience with SQL, Strong understanding of relational databases, Experience designing APIs and infrastructure systems, Strong debugging and troubleshooting skills in cloud environments 📃 Skills: Java, SQL, APIs, CDC, SaaS, Cloud, Databases, DistributedSystems, DataIntegration, DataProcessing, Scheduling, Ingestion 🏢 Description: At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our teams develops in-house connectors to connect with external systems and data warehouses. We are working to connect Snowflake with Fortune 500 companies - in the cloud. In this area you will be working on exposing API, blueprints and frameworks for other developers to create their own connectors. YOUR RESPONSIBILITIES Design and develop data integration and processing applications. These applications replicate data from various data sources (including relational databases, saas, data streams) into Snowflake, following CDC patterns. Develop and extend a robust connector platform to standardise and accelerate the development of connectors, either developed by Snowflake or by third parties. Typical example includes developing a scheduling service ensuring timely execution of tasks and optimal resource allocation. Optimize performance of the ingestion, meet with customers & troubleshoot issues and secure data transfer from external systems. Collaborate with teams across the organization and roles. Create design documents and present them to architects and other stakeholders, including company founders. Lead and mentor a group of engineers Coordinate synchronous and asynchronous communication to ensure goals are met. Collaborate with PMs and customers to understand business requirements, and translate them into connector application solutions. QUALIFICATIONS 5+ years industry experience designing, building and supporting large scale systems. Experience with high performance and scalable software in an internet scale distributed cloud environment. Fluency in Java. Experience with SQL. Good understanding of relational databases. Interest in creating well thought out infrastructure and APIs. Excellent debugging and troubleshooting skills, especially in a cloud environment. Great communication skills, both verbal and written, and an interest in working with a diverse set of peers and external developers. WHY JOIN THE ENGINEERING TEAM AT SNOWFLAKE? Building cutting edge cloud technologies is complex, and our engineering team surmounts the obstacles. As a member of our team, you will: Build an industry-leading data platform that customers love. Learn about and contribute to: Super-robust and secure enterprise SaaS platform that services hundreds of customers and millions of complex queries daily. Highly-scalable and reliable data processing platform that runs on hundreds and thousands of machines. User interfaces bridging the enterprise world with the consumer experience. Join a world-class team of both industry veterans and rising stars. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com This role includes (beside base salary): Bonus: This role is also eligible for 15% annual bonus and benefits package Equity: 30-50% of your annual salary

🏢 Summary: Network Engineer role focused on supporting and improving a large-scale global network infrastructure, including provisioning, monitoring, troubleshooting, and automation tasks. The position involves working with corporate and datacenter networks, routing protocols, wireless technologies, and network security in a fast-paced engineering environment. 🗂️ Requirements: Basic understanding of BGP configuration and management, Knowledge of backbone and datacenter networks, Understanding of wireless technologies, Knowledge of at least one internal routing protocol, Knowledge of corporate networking, Knowledge of TCP/IP, Knowledge of remote access, Strong documentation skills, Strong communication skills, Ability to participate in on-call rotation, Eligibility to work under ITAR regulations 📃 Skills: BGP, TCP/IP, Juniper, Cisco, Aruba, Arista, Routing, Wireless, NAC, Scripting, Automation, Networking 🏢 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: Our Network Engineering team handles a dynamic, constantly growing and evolving global network that provides a reliable, high-performance and secure network behind one of the few products in the world that touches over 1 billion people. The ideal candidate is a Network Engineer who is proficient with the fundamentals, and eager to grow your skills on a global network. RESPONSIBILITIES: - Help to define configuration and architecture standards - Contribute to the qualification of new platforms - Provisioning of network devices in corporate offices and POPs as per documented procedures - Provisioning and management of corporate circuits - Contribute to the continuous improvement of configuration standards and operational procedures - Contribute to the continuous improvement of corporate device monitoring - Liaise with third parties, IT and remote office users to fix and resolve issues - Creation and execution of scheduled changes, process & documentation - Participate in the on call rotation - Maintaining and upgrading existing systems, firmware updates and configurations - Monitoring network performance and ensuring system availability and reliability - Troubleshooting: Analyzing and resolving network hardware and software problems BASIC QUALIFICATIONS: - Basic understanding of BGP configuration and management - Basic knowledge of backbone and datacenter networks - Working understanding of wireless technologies - Working knowledge of at least one internal routing protocol, its configuration and day to day operation - Working knowledge of corporate networking - Working knowledge of TCP/IP - Working knowledge of remote access - Strong documentation and communication skill set PREFERRED SKILLS AND EXPERIENCE: - Familiarity with multiple networking vendors, such as Juniper, Cisco, Aruba, Arista - Familiarity with remote access - Familiarity with network security and NAC - Familiarity with scripting and automation of network operations activities ITAR REQUIREMENTS: To conform to U.S. Government export regulations, applicant must be a U.S. citizen or national, U.S. lawful permanent resident, Refugee, Asylee, or be eligible to obtain the required authorizations from the U.S. Department of State. SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

🏢 Summary: Senior Software Engineer role focused on designing and building AI-powered backend systems that automate healthcare operations while supporting human workflows. The position involves hands-on system architecture, workflow orchestration, distributed systems, and AI process automation in a regulated environment. Remote-first work with required overlap with US Central Time. 🗂️ Requirements: 6+ years of experience building and maintaining production software systems, Strong experience designing and owning complex backend systems, Strong backend engineering skills, Experience with asynchronous, event-driven, or workflow-based distributed systems, Ability to work with 4–5 hour daily overlap with US team, Experience with AI or LLM-based systems and process automation, Strong spoken and written English communication skills, Ability to solve unclear problems with incomplete information, Self-motivated with strong ownership and responsibility 📃 Skills: TypeScript, Node.js, AI, LLM, Claude, Backend, APIs, HIPAA 🏢 Description: Please Note: Overlap with Central US Time required (until 20-21:00 CEST) We are a health technology company that helps older people and their families apply for important eldercare benefits, including Medicaid, Medicare, and VA programs. We work with healthcare, government systems, and people’s daily lives, so accuracy, reliability, and trust are very important. As the number of patients grows from hundreds to thousands, manual work is no longer enough. We are building AI-powered systems to automate routine tasks while keeping people involved for quality checks, difficult cases, and patient safety. Our goal is to make healthcare operations more scalable without losing the human connection. The Role We are looking for a Senior Software Engineer to lead the design and development of systems that combine AI automation with human workflows. This is an important role close to the core business. It is a fully hands-on position with no management duties or direct reports. You will not only build features, but also design systems, define best practices, and guide technical decisions as we grow. You should feel comfortable solving unclear problems, working closely with operations and product teams, and making smart decisions in a regulated environment. This role is a good fit for someone who enjoys system design, building reliable infrastructure, and taking ownership of their work. What You’ll Work On Designing workflow and orchestration systems for complex operations. Creating AI automations that handle routine tasks safely and send difficult cases to humans. Building systems where AI supports human work before, during, and after tasks. Managing long-running workflows that can last days or weeks. Connecting with external systems such as EVV platforms, insurers, government portals, and older messaging tools. Designing confidence scoring, auditing, and rollback systems for AI processes. Improving system reliability, monitoring, and error handling in production. Responsibilities Lead the technical design and development of scalable backend systems. Make and document architecture decisions with clear trade-offs. Create patterns for collaboration between AI systems and human workers. Work closely with operations teams to understand real-world issues and edge cases. Make sure systems are observable, auditable, and safe to run at scale. Identify technical risks early and suggest solutions. Maintain high standards for code quality, testing, and system design. Share knowledge and help improve the team’s technical standards through reviews and collaboration. What We’re Looking For Required 6+ years of experience building and maintaining production software systems. Strong experience designing and owning complex backend systems. Strong backend engineering skills (we use TypeScript and Node.js, but other languages are welcome). Experience with asynchronous, event-driven, or workflow-based distributed systems. Ability to work with a daily 4–5 hour overlap with the US team (until 20:00 or 21:00 Polish time). Comfortable working with unclear problems and incomplete information. Strong spoken and written English communication skills. Self-motivated with a strong sense of ownership and responsibility. Experience working with AI or LLM-based systems and process automation, such as using Anthropic’s API (Claude) or similar tools in business workflows. Nice to Have Experience in healthtech or other regulated industries. Knowledge of HIPAA and healthcare data privacy and security rules. Experience building systems with strict compliance or audit requirements. Experience with human review workflows. Experience integrating with unstable or legacy third-party APIs. Master’s or PhD in Computer Science, Engineering, or a related field. How We Work Remote-first company. Small, experienced teams with high trust and independence. Strong focus on system accuracy, reliability, and long-term maintenance. Practical and thoughtful use of AI, both for internal development and within our product. Direct connection to real users and operational impact.

🏢 Summary: Senior Software Engineer role focused on designing and building scalable backend systems that combine AI automation with human workflows in a regulated healthtech environment. The position involves hands-on system design, workflow orchestration, and development of reliable, auditable AI-powered processes integrated with external platforms. The engineer will lead technical decisions and ensure production-grade reliability, safety, and scalability. 🗂️ Requirements: 6+ years building and maintaining production software systems, Strong experience designing and owning complex backend systems, Strong backend engineering experience, Experience with asynchronous or event-driven distributed systems, Experience with workflow-based systems, Experience integrating AI or LLM-based systems into business workflows, Ability to design scalable, reliable, and auditable systems, Experience working with external or legacy APIs, Ability to overlap 4–5 hours with US time zone, Strong English communication skills 📃 Skills: TypeScript, Node.js, AI, LLM, Anthropic, Claude, APIs, DistributedSystems, EventDriven, Workflows, Backend, Architecture, Monitoring, Testing 🏢 Description: Please Note: Overlap with Central US Time required (until 20-21:00 CEST) We are a health technology company that helps older people and their families apply for important eldercare benefits, including Medicaid, Medicare, and VA programs. We work with healthcare, government systems, and people’s daily lives, so accuracy, reliability, and trust are very important. As the number of patients grows from hundreds to thousands, manual work is no longer enough. We are building AI-powered systems to automate routine tasks while keeping people involved for quality checks, difficult cases, and patient safety. Our goal is to make healthcare operations more scalable without losing the human connection. The Role We are looking for a Senior Software Engineer to lead the design and development of systems that combine AI automation with human workflows. This is an important role close to the core business. It is a fully hands-on position with no management duties or direct reports. You will not only build features, but also design systems, define best practices, and guide technical decisions as we grow. You should feel comfortable solving unclear problems, working closely with operations and product teams, and making smart decisions in a regulated environment. This role is a good fit for someone who enjoys system design, building reliable infrastructure, and taking ownership of their work. What You’ll Work On Designing workflow and orchestration systems for complex operations. Creating AI automations that handle routine tasks safely and send difficult cases to humans. Building systems where AI supports human work before, during, and after tasks. Managing long-running workflows that can last days or weeks. Connecting with external systems such as EVV platforms, insurers, government portals, and older messaging tools. Designing confidence scoring, auditing, and rollback systems for AI processes. Improving system reliability, monitoring, and error handling in production. Responsibilities Lead the technical design and development of scalable backend systems. Make and document architecture decisions with clear trade-offs. Create patterns for collaboration between AI systems and human workers. Work closely with operations teams to understand real-world issues and edge cases. Make sure systems are observable, auditable, and safe to run at scale. Identify technical risks early and suggest solutions. Maintain high standards for code quality, testing, and system design. Share knowledge and help improve the team’s technical standards through reviews and collaboration. What We’re Looking For Required 6+ years of experience building and maintaining production software systems. Strong experience designing and owning complex backend systems. Strong backend engineering skills (we use TypeScript and Node.js, but other languages are welcome). Experience with asynchronous, event-driven, or workflow-based distributed systems. Ability to work with a daily 4–5 hour overlap with the US team (until 20:00 or 21:00 Polish time). Comfortable working with unclear problems and incomplete information. Strong spoken and written English communication skills. Self-motivated with a strong sense of ownership and responsibility. Experience working with AI or LLM-based systems and process automation, such as using Anthropic’s API (Claude) or similar tools in business workflows. Nice to Have Experience in healthtech or other regulated industries. Knowledge of HIPAA and healthcare data privacy and security rules. Experience building systems with strict compliance or audit requirements. Experience with human review workflows. Experience integrating with unstable or legacy third-party APIs. Master’s or PhD in Computer Science, Engineering, or a related field. How We Work Remote-first company. Small, experienced teams with high trust and independence. Strong focus on system accuracy, reliability, and long-term maintenance. Practical and thoughtful use of AI, both for internal development and within our product. Direct connection to real users and operational impact.

🏢 Summary: Software Engineer role focused on developing and operating high-performance networking software for large-scale AI datacenter infrastructure powering GPU clusters and frontier AI models. The position involves building routing, traffic-engineering, and real-time distributed systems software with ownership across the full software lifecycle. Candidates will work on low-latency networking, deployment systems, and large-scale infrastructure reliability. 🗂️ Requirements: Bachelor's degree in computer science, engineering, math, or related field OR 2+ years of professional software development experience, Strong development experience in C or C++, Experience developing and deploying software at scale, Knowledge of networking protocols, Knowledge of distributed systems, Ability to work in fast-paced environments, Strong communication skills, Willingness to work extended hours and weekends when needed 📃 Skills: C, C++, UDP, TCP/IP, RDMA, Networking, DistributedSystems, Linux, CI, HPC 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. The team is small, highly motivated, and focused on engineering excellence. Employees are expected to be hands-on, contribute directly to the mission, demonstrate initiative, and communicate clearly with teammates. ABOUT THE ROLE: At xAI, engineers design, build, and operate Colossus from the ground up, including massive GPU clusters, high-speed interconnect fabric, and the software that enables operation at unprecedented scale. Colossus powers frontier AI models with a custom high-performance datacenter network delivering ultra-low latency and massive bandwidth across hundreds of thousands of GPUs. As a Software Engineer on the Colossus Networking team, you will develop core networking software that maximizes the performance and reliability of the datacenter fabric. The role directly impacts training efficiency, model convergence, and AI infrastructure performance. Engineers own the full lifecycle of software, including design, implementation, deployment, monitoring, and iteration based on real-world performance at scale. The role involves solving problems in distributed systems, high-performance networking, and real-time control of one of the largest AI supercomputers in operation. RESPONSIBILITIES: - Develop routing and traffic-engineering algorithms for the Colossus high-performance datacenter network. - Develop highly reliable, real-time software designed to run on network switches supporting low-latency, high-bandwidth AI training infrastructure. - Participate in and lead architecture, design, and code reviews. - Develop prototypes and run experiments to validate design decisions at small and full-cluster scale. - Build tools for software development, deployment, data analysis, visualization, and testing across virtualized environments, hardware-in-the-loop setups, and production clusters. - Deploy reliable software updates through continuous integration and release systems with rigorous testing and monitoring. BASIC QUALIFICATIONS: - Bachelor's degree in computer science, engineering, math, or related technical discipline; OR 2+ years of professional software development experience in lieu of a degree. - Strong development experience in C or C++. PREFERRED SKILLS AND EXPERIENCE: - Strong professional experience writing high-performance C/C++ in production environments. - Experience developing, debugging, and deploying software that runs at scale in real-world systems. - Deep knowledge of networking protocols including UDP, TCP/IP, and RDMA. - Knowledge of distributed systems and large-scale datacenter fabrics. - Background in real-time systems, high-performance computing, low-latency networking, or resource-constrained environments. - Creative problem-solving ability with strong analytical and engineering skills. - Excellent written and verbal communication skills. - Ability to thrive in a fast-paced, dynamic environment with evolving requirements. - Experience with security considerations in large-scale distributed systems. ADDITIONAL REQUIREMENTS: - Must be willing to work extended hours and weekends as needed. COMPENSATION AND BENEFITS: - Base salary range: $180,000 - $440,000 USD. - Equity compensation. - Comprehensive medical, vision, and dental coverage. - 401(k) retirement plan. - Short-term and long-term disability insurance. - Life insurance. - Additional discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.