Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

State Street's Cyber Data & Analytics (CyberDNA) team is seeking a Lead AI Security Automation Engineer to 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 global threat actors by leading the development of foundational platforms and capabilities for intelligent security operations at enterprise scale.

Responsibilities

Build, lead, and mentor a high-performing team of AI Automation Engineers focused on advancing cybersecurity operations through automation and AI-driven innovation.
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 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 senior & 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, 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.
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, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt lifecycle management.
Experience implementing AI evaluation, testing, monitoring, and observability frameworks to measure model quality, reliability, performance, and safe operation in production environments.
Strong API design and integration experience, including the development of secure, reusable, and scalable platform services that enable enterprise-wide adoption of AI capabilities.
Demonstrated technical leadership skills with a track record of mentoring engineers, driving architectural decisions, influencing technology strategy, and collaborating effectively with cross-functional stakeholders.
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.
Strong understanding of responsible AI principles, including data privacy, security, governance, resiliency, and risk management.
Deep understanding of cybersecurity functions to support threat detection engineering, threat hunting, offensive/defensive security, Threat intelligence and SOC operations.
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 through virtual collaboration, fostering strong partnerships, driving technical outcomes, and building effective relationships across engineering, security, and business organizations.
Deep understanding of CI/CD tools (Jenkins, Harness, Spinnaker, Argo CD, etc.) and methodology, 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 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 (AWS, Azure, GCP)
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
Security
Governance
Resiliency
Risk management
Cybersecurity functions
Threat detection engineering
Threat hunting
Offensive security
Defensive security
Threat intelligence
SOC operations
Cybersecurity operations
Incident response
Security analytics
Security automation
Virtual collaboration
CI/CD tools (Jenkins, Harness, Spinnaker, Argo CD)
CI/CD methodology
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 frameworks
Evaluation frameworks
Data governance
Model risk management

Location

Local time

Work Type

Hybrid
Full-time

Experience Level

10+ years of professional software engineering experience
4+ years of experience developing AI, Machine Learning, or Generative AI solutions
Demonstrated success designing and deploying enterprise-scale applications and platforms
Experience developing cybersecurity, analytics, or operational intelligence solutions

Education Level

Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Cybersecurity, or a related discipline

Salary/Compensations

$120,000 - $217,500 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

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability.
We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential.
As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most.
Join us in shaping the future.

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.