Senior Security Consultant, Threat Intelligence, Mandiant

🏢 Summary: Security Engineer role focused on securing cloud software, systems, network boundaries, and sensitive data. The position performs security assessments, code reviews, vulnerability research and testing, incident remediation, and secure-design guidance across varied technology stacks. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of security assessments, security design reviews, or threat modeling experience, 5 years of security engineering, computer and network security, and security protocols experience, 5 years of coding experience in one or more general-purpose languages, 1 year of technical team leadership or enterprise technical risk-analysis leadership experience 📃 Skills: Security, Networking, Threat-modeling, Coding, Protocols, Fuzzing, Pentesting, SDN, IETF, Firewalls, DNS, Reverse-engineering, Static-analysis 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 5 years of experience with security assessments, security design reviews, or threat modeling. • 5 years of experience with security engineering, computer and network security, and security protocols. • 5 years of coding experience in one or more general-purpose languages. • 1 year of experience leading teams in a technical capacity or leading technical risk analysis in an enterprise environment. Preferred qualifications • Experience in security testing and pen-testing. • Experience in network security, including network protocols, software-defined networking (SDN), Internet Engineering Task Force (IETF), firewalls, or DNS security. About the job Security Engineers help protect network boundaries, harden computer systems and network devices against attacks, and provide security services for highly sensitive data such as passwords and customer information. The role works directly with network equipment, actively monitors systems for attacks and intrusions, and partners with software engineers to identify and remediate security flaws and vulnerabilities. The Cloud CISO Security Engineering team helps ensure products and underlying infrastructure are designed to the highest security standards. The team improves product teams' ability to build secure products by design and by default through patterns, tools, frameworks, and embedded security leadership. As an information security engineer, you will perform technical security assessments, code reviews, and vulnerability testing to highlight risk and help teams and partners improve security across a wide variety of software designs and technology stacks. Responsibilities • Perform security reviews; research and reproduce vulnerabilities; design secure protocols and systems; and write tests and fuzzers. • Review designs for vulnerabilities through one-time reviews and longer-term engagements. • Respond to vulnerabilities with reproductions, mitigations, and hardening; identify vulnerability patterns and design them out. • Review and develop secure operational practices and provide security guidance to engineers and support staff. • Identify vulnerabilities using reverse engineering, fuzzing, and static analysis; architect scalable solutions.

🏢 Summary: Security Advisor role leading enterprise security transformations across North America and Latin America. The position focuses on maturing Security Operations through SIEM/SOAR, multi-cloud threat visibility, detection engineering, and AI-driven automation while advising executive stakeholders. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 7 years of experience architecting, developing, or maintaining secure cloud solutions, Experience with system design or reading code, Experience with SecOps offerings and the cybersecurity vendor landscape, Fluent English and Spanish communication skills 📃 Skills: SIEM, SOAR, SecOps, Java, C++, Python, Cloud, GCP, AI, CSPM, SaaS, GTI, CEP 🏢 Description: Qualifications Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 7 years of experience architecting, developing, or maintaining secure cloud solutions. • Experience in either system design or reading code (e.g., Java, C++, Python). • Experience in SecOps product offerings (e.g., SIEM, SOAR) and the broader vendor space in cybersecurity. • Ability to communicate in English and Spanish fluently to engage with local stakeholders. Preferred qualifications • Experience in security operations, security architecture, or security engineering. • Experience in the implementation and ongoing oversight of SIEM and SOAR deployments. • Familiarity with AI-assisted tools, such as prompt-based threat hunting, automated query translation, natural language investigation, or Agentic AI. • Demonstrated foundational understanding in cloud computing technologies. • Proven track record of success in meeting or exceeding client deliverables and expectations. • Strong client leadership, communication, and people management skills. About the job As a Security Advisor, you will lead strategic enterprise clients across North America and Latin America through modern security transformations. You will guide organizations in maturing their Security Operations, with deep expertise in SIEM and SOAR technologies. As a trusted advisor, you will partner with security leaders to accelerate adoption and drive strategic defense initiatives. You will leverage generative AI and advanced automation to streamline threat detection, investigation, and response, helping clients stay ahead of emerging threats. Responsibilities • Manage a portfolio of Tier 1 global accounts through onboarding and post-onboarding, serving as a trusted advisor to customer executives, driving SaaS Value Realization, and navigating critical client escalations. • Lead detection engineering initiatives and design advanced SOAR automation workflows to transition clients from manual processes to scalable, automated response playbooks. • Architect comprehensive multi-cloud ingestion plans (e.g., GCP) to ensure unified threat visibility and systematically reduce customer security risk. • Guide clients in adopting security capabilities, demonstrating how to leverage generative AI and Agentic Security Operations Center (SOC) workflows to modernize their security posture. • Maintain deep technical expertise through continuous enablement on Google Security Operations (SecOps), Google Threat Intelligence (GTI), Chrome Enterprise Premium (CEP), Cloud Security Posture Management (CSPM) tooling, and GCP architecture to remain at the forefront of cybersecurity trends.

🏢 Summary: Lead manufacturing test engineering for hardware systems, managing a team and developing scalable test strategies, automation, and process improvements. The role addresses complex product failures through RCCA, data collection, and manufacturing-process qualification for server, storage, and networking hardware. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience, 10 years of test engineering experience in electronics manufacturing, 8 years of people management experience, Python, Bash, and Shell scripting experience for product-specific test plans and test execution 📃 Skills: Python, Bash, Shell, RCCA, ICT, BSCAN 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience. • 10 years of experience in Test Engineering in electronics manufacturing. • 8 years of experience in people management. • Experience coding in Python, Bash, and Shell scripting to generate product-specific test plans and execute testing accordingly. Preferred qualifications • Experience in manufacturing, quality, or product engineering for hardware technology and systems. • Experience working with server, storage, and networking products, especially AI and ML servers, racks, and integration. • Experience with test station bring-up, gauge R&R/correlation, and partner or agreement manufacturing (ODM, OEM, JDM). • Experience managing manufacturing test hardware using custom electronics, fixturing, instrumentation, and defining test strategy, test automation, test optimization, and scaling test capacity. • Experience with design for test and structural tests such as ICT/BSCAN, Board- and System-level Functional Tests. • Ability to drive improvement of test systems and processes for scaling test capacity. About the job Join a team developing custom silicon solutions that support direct-to-consumer hardware products. Contribute to next-generation hardware experiences focused on performance, efficiency, and integration, while supporting the technical infrastructure behind data centers, platforms, and networks. Responsibilities • Lead a team; set and communicate individual and team priorities that support organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Apply Root Cause Corrective Action (RCCA) fundamentals and collaborate with teams to analyze failures and resolve issues. • Define and execute data-collection activities for highly complex technical issues. • Drive process design, optimization, and qualification activities for manufacturing processes involving components, parts, or products.

🏢 Summary: Technical role focused on building AI-driven financial experiences by integrating third-party tools and agent workflows into an AIX orchestration layer. The position develops scalable, low-latency Generative UI capabilities and personalized financial insights using user signals, while leading architecture and delivery from discovery through production. 🗂️ Requirements: Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience, 5 years of software development experience, Experience with C++, Java, Kotlin, Python, or another general-purpose programming language, Experience developing, prompt-tuning, fine-tuning, or orchestrating LLM and generative AI systems, Experience with algorithms, Experience architecting backend or infrastructure systems 📃 Skills: C++, Java, Kotlin, Python, LLMs, AI, Algorithms, Backend, Infrastructure, MCP, MaRS, Agency, GenUI 🏢 Description: Minimum qualifications: • Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience. • 5 years of software development experience in one or more general-purpose programming languages (e.g., C++, Java, Kotlin, Python). • Experience developing with, prompt-tuning, fine-tuning, or orchestrating Large Language Models (LLMs) and generative AI systems. • Experience with algorithms and architecting backend or infrastructure systems. Preferred qualifications: • Experience with tool execution pipelines, agentic workflows, function calling, or Model Context Protocol (MCP) integration. • Experience working with Generative UI pipelines, adaptive design architectures, or dynamic component rendering systems. • Familiarity with Google Search Next infrastructure, specifically MaRS, Agency, and GenUI ecosystem components. • High interest in personal finance, market intelligence, fintech, or complex transactional domains where high precision and factuality are paramount. Responsibilities: • Lead technical execution for connecting external third-party tools and partner agents into an AIX orchestration layer utilizing the Model Context Protocol (MCP). • Build scalable, low-latency Generative UI capabilities on top of Core Search Next platforms, including MaRS, Agency, and the GenUI framework, to transform raw financial output into actionable, interactive user experiences. • Integrate Zero-Party (0P), First-Party (1P), and Third-Party (3P) user signals to deliver tailor-made financial insights while setting new standards for strict factuality, multi-turn conversation context, and high-utility helpfulness. • Identify engineering gaps, set technical roadmap priorities, and guide initiatives from initial discovery through production deployment. • Build strong relationships with cross-functional partners in Product Management, User Experience, Research, Quality, and External Partner Integration to align technical goals with product strategy.

🏢 Summary: Lead Google Cloud AI Research engineering teams developing and deploying large-scale generative AI solutions. The role combines technical strategy, ML infrastructure optimization, system design, code development, and people leadership across multiple teams and locations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8+ years of software development experience, 5+ years leading ML design and ML infrastructure optimization, 3+ years in technical leadership, 2+ years with state-of-the-art GenAI techniques or related concepts, 2+ years of people management or team leadership experience 📃 Skills: Python, C, C++, Java, JavaScript, ML, GenAI, LLMs, Multimodal, Vision, Deployment, Evaluation, Debugging, Finetuning 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 3 years of experience in a technical leadership role. • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 3 years of experience working in an organization involving cross-functional or cross-business projects. About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They manage project goals, contribute to product strategy, develop their teams, and help engineers optimize their code. This role manages engineers across multiple teams and locations, a large product budget, and the deployment of large-scale projects across multiple international sites. The Google Cloud AI Research team addresses AI challenges across industries including technology, healthcare, finance, and retail, conducting research with scientific and real-world impact and collaborating with product teams to bring innovations to customers. Responsibilities • Set and communicate team priorities that support broader organizational goals; align strategy, processes, and decision-making across teams. • Set clear expectations based on individuals’ levels and roles; meet regularly to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical vision and roadmap for one or more teams; evolve the roadmap for future requirements and infrastructure needs. • Design, guide, and vet system designs; write product or system development code to solve ambiguous problems. • Lead the design of GenAI solutions, optimize ML infrastructure, and guide data preparation and model optimization strategies.

🏢 Summary: Senior technical leadership role focused on designing and scaling an AI-powered DevAI platform for Ads engineering workflows. The position leads foundational infrastructure, custom agents, and AI-forward architecture initiatives across Ads organizations. 🗂️ Requirements: Bachelor’s degree in Computer Science, Mathematics, engineering, or equivalent practical experience, 15 years of professional engineering experience 📃 Skills: DevAI, LLMs, GoogleAds, AdSense, Infrastructure, Architecture, Automation 🏢 Description: Qualifications Minimum qualifications • Bachelor’s degree in Computer Science, Mathematics, or another relevant engineering discipline, or equivalent practical experience • 15 years of professional engineering experience Preferred qualifications • Master’s degree in Computer Science, Mathematics, or Engineering • Experience providing technical leadership across a larger organization and motivating stakeholders at all levels through a shared vision and purpose • Knowledge of Google Ads products, relevant product and user ecosystems, and competitor products • Ability to balance detailed technical guidance with big-picture strategy • Thought leadership to identify and design problems aligned with principal-engineer scope and complexity, with a desire to solve difficult engineering problems • Demonstrated technical innovation in large, complex, cross-functional engineering environments About the job The Ads DevAI Platform team enables Ads to use LLMs to accelerate optimizations, infrastructure migrations, resource efficiency, and more. The team builds infrastructure and marquee agents that enable AI-powered acceleration for Ads engineering workflows. This role provides senior technical leadership to design and accelerate Ads engineering workflows using AI. The broader Ads organization builds advertising products across search, display, shopping, travel, and video advertising, as well as analytics, creating trusted experiences between people and businesses through useful ads and effective advertiser tools. Responsibilities • Design and build foundational DevAI infrastructure for Ads, ensuring extensibility, broad applicability, and maximum ROI across business verticals and functions • Provide technical leadership and oversight for cross-cutting Ads internal AI projects, including marquee agents, AI-friendly infrastructure, and strategic DevAI initiatives • Drive the transition to AI-forward architecture and self-managing codebases through agentic, evaluation-driven development, skills, and context integration • Lead the technical strategy and development of the DevAI platform and custom agents, while mentoring Business Account Managers AI across Ads infrastructure organizations • Collaborate with technical leaders across Ads PAGs, Core, and GDM to influence roadmaps, technical direction, and the broader Buying platforms and Ads vision

🏢 Summary: Research-focused Software Engineer role advancing large language model and information retrieval capabilities for Gemini, Search, and related products. The position combines model evaluation, multi-stage training and practical modeling innovations, with deployment of research advances alongside Search and YouTube teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, a related technical field, or equivalent practical experience, 3 years of machine learning experience focused on Large Language Models or Information Retrieval, 3 years of software engineering experience using Python, C++, JAX, or PyTorch, Experience implementing multi-stage training pipelines or algorithms 📃 Skills: Python, C++, JAX, PyTorch, LLMs, IR, MachineLearning 🏢 Description: Minimum qualifications • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience. • 3 years of experience in machine learning, with a focus on Large Language Models (LLMs) or Information Retrieval (IR). • 3 years of experience with software engineering in Python, C++, JAX, or PyTorch programming, including experience implementing multi-stage training pipelines or algorithms. Preferred qualifications • Experience developing Reinforcement Learning (RL) algorithms, automated evaluation systems, or LLM reflection and reasoning frameworks. • Experience with competitive programming, mathematics competitions (e.g., ICPC, IOI, IMO), or a track record of developing novel algorithms. • Experience rapidly prototyping and iterating on complex systems, generative AI models, or multi-stage pipelines. • Experience collaborating with product engineering teams to deploy machine learning models or research innovations into large-scale production environments (e.g., Search, Recommendation Systems). • Track record of learning new software tools, frameworks, and codebases quickly to solve complex technical obstacles. About the job Research-focused Software Engineers create experiments, prototype implementations, and design new architectures for real-world challenges such as artificial intelligence, data mining, natural language processing, hardware and software performance analysis, compilers for mobile platforms, and core search. The role includes large-scale testing and rapid deployment of promising ideas, while contributing to the wider research community through university partnerships and published papers. Responsibilities • Uncover strategic opportunities at the intersection of Gemini, Search, factuality, continual learning, deep research, and domain internalization. • Analyze models and model-driven products beyond current leaderboards; understand complex problem spaces and create new ways to measure ideal behavior. • Use empirical findings to develop practical interventions and modeling innovations that improve models across downstream surfaces. • Collaborate with product teams such as Search and YouTube to scale research innovations into production environments, optimizing for quality and efficiency.

🏢 Summary: Lead the architecture and scaling of AI/ML infrastructure for YouTube Ads creative automation. The role focuses on high-throughput distributed systems, GenAI media-processing pipelines, experimentation platforms, and technical leadership across product and research teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience, 8 years of software development experience, 5 years of software product testing and launch experience, 5 years building large-scale infrastructure, distributed systems, networks, compute, storage, or hardware architecture, 3 years of software design and architecture experience, Experience designing or deploying machine-learning infrastructure or platforms 📃 Skills: Python, TensorFlow, PyTorch, Cloud, Distributed, Infrastructure, Architecture, Algorithms, MachineLearning, DeepLearning, GenAI 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing and launching software products. • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience with software design and architecture. • Experience designing or deploying machine learning (ML) infrastructure or platforms. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 3 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. • Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud/distributed data technologies. About the job Develop next-generation technologies that operate at massive scale. Work on a project critical to business needs, with opportunities to switch teams and projects as priorities evolve. Bring ideas across areas including distributed computing, large-scale system design, networking, data storage, artificial intelligence, and more. Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions. The YouTube Ads Creative Optimization (YACO) team develops Creative Automation applications that drive advertiser value with minimal advertiser effort by leveraging AI technologies. The team operates at the intersection of Ads, YouTube, and Research. Responsibilities • Serve as the technical leader responsible for architecting, scaling, and steering next-generation infrastructure that powers AI/ML applications. • Operate at the intersection of Ads, YouTube, and GenAI research to build high-throughput systems enabling seamless creative generation and optimization. • Define the technical roadmap and architect scalable foundational infrastructure, including creative data engines, generation and rendering pipelines, and agentic orchestration frameworks. • Design and optimize distributed systems for complex GenAI and heavy media-processing workloads. • Build and mature experiment and learning infrastructure to accelerate model training, evaluation, and rapid deployment. • Partner with Product Management, Research, and executive leadership to align infrastructure capabilities with long-term business goals. • Guide, mentor, and elevate executive and junior engineers, fostering technical excellence and execution.

🏢 Summary: Software engineering role focused on building, testing, and maintaining scalable Google Search products, with a strong emphasis on GenAI solutions and ML infrastructure. The position involves full-stack engineering, design and code reviews, production issue resolution, and evaluating GenAI techniques for large-scale user experiences. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of Python or C++ programming experience, 3 years of software product testing, maintenance, or launch experience, 1 year of software design and architecture experience, 3 years of ML infrastructure experience, 1 year of GenAI techniques or GenAI-related concepts experience 📃 Skills: Python, C++, ML, GenAI, LLMs, Multimodal, Vision, Deployment, Evaluation, Optimization, Debugging, Architecture 🏢 Description:

🏢 Summary: Customer Engineer role partnering with sales teams to design and demonstrate Google Cloud solutions for customers. The position leads technical discovery, demos, pilots, solution architecture, and delivery planning to win and expand cloud workloads. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 6 years of cloud computing experience, 6 years of presentation delivery experience, Experience presenting to technical stakeholders and executive leaders 📃 Skills: Cloud, GoogleCloud, A2A, LangGraph, CrewAI, AutoGen, VertexAI, LLM, TTFT, MCP, Authentication, Quantization 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 6 years of experience with cloud computing and delivering presentations. • Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications • Experience navigating AI infrastructure consumption models and optimizing high-throughput training/inference clusters. • Experience implementing multi-agent systems using frameworks such as A2A, LangGraph, CrewAI, and AutoGen. • Experience navigating the startup life cycle, from initial prototyping with AI Studio to scaling and achieving product-market fit on Vertex AI. • Experience working with, and a passion for, the high-growth startup ecosystem and its typical rapid-scaling issues. • Knowledge of LLM-native performance metrics, including TTFT, tokens/sec, and cost-per-request, and techniques for optimizing state management, quantization, and provisioned throughput. • Ability to implement secure agentic workflows incorporating MCP, tool-calling, and enterprise-grade authentication. About the job As a Customer Engineer, you will partner with technical sales teams to differentiate cloud solutions for customers. You will serve as the customer’s primary technical partner and trusted advisor, leading technical conversations to understand business issues. You will troubleshoot technical questions and roadblocks, participate in proofs of concept and demos, and architect cross-pillar cloud solutions. You will drive the technical win, define delivery and consumption plans, and present practical solutions to technical and business leaders. You will identify, pursue, and win new business workloads while expanding existing ones. The role requires broad technical expertise across infrastructure modernization, application modernization, data analytics, and related areas, combined with sales expertise, market knowledge, and direct technical engagement. Responsibilities • Develop and own the technical account plan and strategy, participating in planning and supporting targeted sales motions. • Combine sales, programming, and solutions architecture expertise to prove the value of the cloud portfolio through complex demos, pilots, and in-depth workshops. • Architect cross-pillar solutions, drive technical wins, and define initial delivery plans for customers; continue to lead technical engagement during the solution phase. • Facilitate the post-sales transition by supporting pricing activities and transitioning the final delivery plan to implementation teams. • Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration, or implementation phases.