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About the Role

State Street's Cyber Data & Analytics (CyberDNA) team is seeking a Senior AI Security Automation Engineer to help shape the next generation of cybersecurity data, analytics, and AI-powered platforms. This role is critical in protecting State Street, its clients, and partners from sophisticated cyber threats by developing advanced data platforms and AI-driven solutions.

Responsibilities

• Drive 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 services in AWS, Azure and GCP using containers and serverless patterns, event-driven messaging, and distributed data stores.
• Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls.
• 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.
• Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle.
• Mentor junior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership.
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity.
• Apply knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation.

Requirements

• Demonstrated experience architecting, developing, and deploying production-grade Generative AI and Large Language Model (LLM) based solutions.
• Strong software engineering fundamentals with expertise in designing and delivering cloud-native applications and services.
• Proven experience building highly scalable distributed systems utilizing asynchronous processing, event-driven architectures, durable messaging, and high-performance data access patterns.
• Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions.
• Experience implementing AI evaluation, testing, monitoring, and observability frameworks.
• Strong API design and integration experience.
• Demonstrated technical leadership skills with a track record of mentoring engineers and driving architectural decisions.
• Hands-on experience utilizing enterprise-approved AI-assisted software development tools.
• Strong understanding of responsible AI principles, including data privacy, security, governance, resiliency, and risk management.
• Deep understanding of cybersecurity data sources and their application in security monitoring, analytics, and automation.
• Experience working with Security Information and Event Management (SIEM) platforms and cybersecurity analytics solutions.
• Strong understanding of cybersecurity operations, including threat detection, incident response, threat hunting, security analytics, and security automation.
• Proven ability to lead and influence geographically distributed teams.
• Deep understanding of CI/CD tools and methodology, with production experience in designing and implementing CI/CD pipelines.
• Strong software development and automation skills with demonstrated experience in Python, JavaScript/TypeScript, Rust, Go (Golang), Bash, and PowerShell.
• Proven ability to lead complex technical initiatives while remaining deeply hands-on.
• Experience developing cybersecurity, analytics, or operational intelligence solutions.
• 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.

Skills

• Generative AI
• Large Language Models (LLM)
• Agentic workflows
• Intelligent agents
• Enterprise tool integration
• Cloud-native applications
• Containers
• Serverless architectures
• Public cloud platforms
• Distributed systems
• Asynchronous processing
• Event-driven architectures
• Durable messaging
• High-performance data access
• Retrieval-Augmented Generation (RAG)
• Embeddings
• Semantic search
• Knowledge grounding
• Context engineering
• Prompt optimization
• Prompt lifecycle management
• AI evaluation
• AI testing
• AI monitoring
• AI observability
• API design
• API integration
• Platform services
• Technical leadership
• Mentoring engineers
• Architectural decisions
• Technology strategy
• Cross-functional collaboration
• AI-assisted software development tools
• Secure coding practices
• Automated testing
• Responsible AI principles
• Data privacy
• AI security
• AI governance
• AI resiliency
• AI risk management
• Cybersecurity data sources
• Endpoint telemetry
• Network telemetry
• Application telemetry
• Cloud telemetry
• System telemetry
• Security monitoring
• Security analytics
• Security automation
• Security Information and Event Management (SIEM)
• Cybersecurity analytics solutions
• Threat detection
• Incident response
• Threat hunting
• Security analytics
• Security automation
• Virtual collaboration
• CI/CD tools
• Jenkins
• Harness
• Spinnaker
• Argo CD
• CI/CD pipelines
• Python
• JavaScript/TypeScript
• Rust
• Go (Golang)
• Bash
• PowerShell
• LangGraph
• Semantic Kernel
• CrewAI
• AutoGen
• LangChain
• Databricks
• Snowflake
• Spark
• Kafka
• Delta Lake
• Iceberg
• Airflow
• Vector databases
• Enterprise RAG platforms
• MLOps
• LLMOps
• AI observability
• Data governance
• Model risk management

Location

• Primary location specified

Work Type

• Hybrid
• Full-time

Experience Level

• Senior
• 7+ years of professional software engineering experience
• 3+ years of experience developing AI, Machine Learning, or Generative AI solutions

Education Level

• Master’s or bachelor’s degree in computer science, Software Engineering, Artificial Intelligence, Data Science, Cybersecurity, or a related discipline

Salary/Compensations

• $120,000 - $202,500 Annual

Benefits

• Retirement savings plan (401K) with company match
• Insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
• Paid-time off including vacation, sick leave, short term disability, and family care responsibilities
• Access to Employee Assistance Program
• Incentive compensation including eligibility for annual performance-based awards
• Eligibility for certain tax advantaged savings plans

About the Company

• Institutional investors rely on State Street to help them manage risk, respond to challenges, and drive performance and profitability.
• State Street is committed to fostering an environment where every employee feels valued and empowered to reach their full potential.
• Benefits include inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks.

Equal Opportunity

• As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.