Lead AI Security Automation Engineer, VP
About The Position
State Street’s Cyber Data & Analytics (CyberDNA) team is seeking a Lead AI Security Automation Engineer to shape cybersecurity data, analytics, and AI-powered platforms. Working with Global Cyber Security, Infrastructure Teams, and Enterprise Continuity Services, the role develops data platforms, intelligent automation, and engineering capabilities that enable faster, AI-driven security decisions and strengthen the firm’s ability to detect, prevent, and respond to cyber threats. The role leads the development of foundational platforms and capabilities for enterprise-scale, secure, governed AI adoption in cybersecurity. It combines artificial intelligence, cybersecurity, data engineering, and full-stack software development. The successful candidate will establish and lead a team of AI engineers delivering AI platforms, autonomous agents, security automation, and data-driven applications. This is a hands-on technical leadership position responsible for designing and delivering production-grade agentic AI systems, cloud-native platforms, integrations, and engineering standards. It also involves mentoring engineers, guiding architecture and technical direction, and improving cybersecurity operations through intelligent automation. The role has an 8 AM–5 PM local work shift, with occasional Level 3 escalation resolution, and requires an in-office presence of 2–4 days per week under the hybrid work policy.
Requirements
- 10 or more years of professional software engineering experience.
- 4 or more years of experience developing AI, machine learning, or generative AI solutions.
- Demonstrated experience architecting, developing, and deploying production-grade generative AI and LLM-based solutions, including agentic workflows, intelligent agents, and enterprise tool integration frameworks.
- Strong software engineering fundamentals and experience delivering cloud-native applications and services using containers, serverless architectures, and modern public cloud platforms.
- Experience building scalable distributed systems using asynchronous processing, event-driven architectures, durable messaging, and high-performance data access patterns.
- Hands-on expertise developing RAG solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt lifecycle management.
- Experience implementing AI evaluation, testing, monitoring, and observability frameworks for quality, reliability, performance, and safe production operation.
- Strong API design and integration experience, including secure, reusable, scalable platform services for enterprise AI adoption.
- Technical leadership experience mentoring engineers, driving architecture decisions, influencing technology strategy, and collaborating with cross-functional stakeholders.
- Hands-on experience with enterprise-approved AI-assisted software development tools, validating outputs through secure coding practices, peer review, and automated testing.
- Understanding of responsible AI principles, including data privacy, security, governance, resiliency, and risk management.
- Deep understanding of cybersecurity functions supporting threat detection engineering, threat hunting, offensive and defensive security, threat intelligence, and SOC operations.
- Understanding of cybersecurity operations, including threat detection, incident response, threat hunting, security analytics, and security automation.
- Ability to lead and influence geographically distributed teams through virtual collaboration and build partnerships across engineering, security, and business organizations.
- Deep understanding of CI/CD tools and methodology, with production experience designing and implementing reliable pipelines that support frequent releases.
- Strong software development and automation skills with demonstrated experience in Python, JavaScript/TypeScript, Rust, Go, Bash, and PowerShell.
- Demonstrated success designing and deploying enterprise-scale applications and platforms.
- Experience developing cybersecurity, analytics, or operational intelligence solutions.
Nice To Haves
- Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Cybersecurity, or a related discipline.
- Experience with LangGraph, Semantic Kernel, CrewAI, AutoGen, LangChain, or similar frameworks.
- Experience with Databricks, Snowflake, Spark, Kafka, Delta Lake, Iceberg, and Airflow.
- Experience with vector databases, semantic search, and enterprise RAG platforms.
- Experience implementing MLOps, LLMOps, AI observability, and evaluation frameworks.
- Knowledge of Responsible AI, data governance, and model risk management.
Responsibilities
- Build, lead, and mentor a high-performing team of AI Automation Engineers.
- Lead the architecture and hands-on delivery of scalable, reliable agentic AI platforms for security workflows.
- Design and build production-grade AI systems, including agents, skills, memory patterns, guardrails, and tool-use orchestration.
- Architect retrieval and context-engineering approaches, including embeddings, semantic search, grounding, summarization, and prompt/version management.
- Engineer cloud-native AI solutions across AWS, Azure, and GCP using containers, serverless patterns, event-driven messaging, and distributed data stores.
- Optimize platform latency, throughput, scalability, caching, context efficiency, and cost controls.
- Build governed APIs and integrations connecting AI capabilities to security platforms, tools, and business processes.
- Establish evaluation, research, regression testing, and observability frameworks to improve quality and agent behavior.
- Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle.
- Mentor senior and junior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership.
- Use enterprise-authorized AI coding-assistance tools to improve code quality, delivery speed, and productivity, validating outputs through peer review, automated testing, and secure coding standards.
- Apply software development lifecycle tools and enterprise-authorized AI-assisted development and automation capabilities to improve the value realized by automation.
- Lead complex technical initiatives while remaining deeply hands-on.
- Support operational incidents through occasional Level 3 escalation resolution.
Benefits
- Retirement savings plan (401K) with company match.
- Insurance coverage including basic life, medical, dental, vision, long-term disability, and optional additional coverages.
- Paid time off, including vacation, sick leave, short-term disability, and leave for family care responsibilities.
- Access to an Employee Assistance Program.
- Incentive compensation, including eligibility for annual performance-based awards, with stated exclusions for certain sales roles.
- Eligibility for certain tax-advantaged savings plans.
- Inclusive development opportunities.
- Flexible work-life support.
- Paid volunteer days.
- Employee networks.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
