AI Security Automation Engineer-Officer

Who We Are Looking For

State Street's Cyber Data & Analytics (CyberDNA) team is seeking an AI Security Automation Engineer to join our team to help shape the next generation of cybersecurity data, analytics, and AI-powered platforms. Partnering closely with Global Cyber Security teams, Infrastructure Teams, and Enterprise Continuity Services, this team develops advanced data platforms, intelligent automation solutions, and engineering capabilities that enable cybersecurity teams to make faster, AI-driven decisions and strengthen the firm's ability to detect, prevent, and respond to evolving cyber threats.

Through innovation in AI, analytics, and automation, CyberDNA team plays a critical role in protecting State Street, its clients, and its partners from increasingly sophisticated global threat actors. This role sits at the intersection of Artificial Intelligence, Cybersecurity, Data Engineering, and Full-Stack Software Development, with a primary focus on enabling secure, scalable, and governed AI adoption across the enterprise for supporting Cyber Security functions.

The successful candidate will be part of a global AI security automation engineering team focused on delivering next-generation AI platforms, autonomous agents, security automation solutions, and data-driven applications that strengthen cyber resilience, accelerate innovation, and transform cybersecurity operations through intelligent automation.

• Build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration
• Build retrieval and context-engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management
• Engineer cloud-native AI services in AWS, Azure and GCP using containers and serverless patterns, event-driven messaging, and distributed data stores
• Build well-governed APIs and integrations that connect AI capabilities to security platforms, tools, and business processes
• Establish evaluation, research, regression testing, and observability frameworks to continuously improve quality and agent behavior
• Follow defined engineering standards for reliability, security, and safe AI operation across the platform lifecycle
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

• Experience developing, and deploying production-grade Generative AI and Large Language Model (LLM) based solutions, including agentic workflows, intelligent agents, and enterprise tool integration frameworks.
• Strong software engineering fundamentals with expertise in designing and delivering cloud-native applications and services leveraging containers, serverless architectures, and modern public cloud platforms.
• Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt lifecycle management.
• Hands-on experience utilizing enterprise-approved AI-assisted software development tools to accelerate application delivery, improve code quality, streamline testing and enhance documentation, while ensuring outputs are validated through secure coding practices, peer review, and automated testing.
• Ability to collaborate and work with geographically distributed team members through virtual collaboration, fostering strong partnerships, driving technical outcomes, and building effective relationships across engineering organizations.
• Strong software development and automation skills with experience in Python, JavaScript/Type Script, Rust, Go (Golang), Bash, and Power Shell.
• Lang Graph, Semantic Kernel, CrewAI, Auto Gen, Lang Chain, or similar frameworks.
• Spark, Kafka, Delta Lake, Iceberg, and Airflow.
• Experience with vector databases, semantic search, and enterprise RAG platforms.

• Master’s or bachelor’s degree in computer science, Software Engineering, Artificial Intelligence, Data Science, Cybersecurity, or a related discipline.
• 1-2+ years of professional software engineering experience.
• 1+ years of experience developing AI, Machine Learning, or Generative AI solutions.

• Work shift is 8 AM - 5 PM local time with occasional Level 2-3 escalation resolution to support operational incidents
• This hybrid role includes an in-office presence requirement of 2-4 days per week, consistent with the…