Role purpose
This is a hands-on role for an engineer who leads by building. You'll lead engineering on a multi-year programme to modernize and migrate a large portfolio of middle-office applications to AWS. You'll write production code across primarily front end (ReactJS front ends, TypeScript, NodeJS, npm/pnpm etc., DevOps pipelines). You'll also set up and run the UI team's AI-augmented delivery model, using AI agents and assistants to speed up discovery, code conversion, testing and deployment while meeting the control standards a global custodian needs.
Key responsibilities
Hands-on UI engineering
•Build ReactJS front ends that replace legacy desktop and GWT/PowerBuilder UIs, including state management, component libraries, SSO/MFA integration and accessibility.
•Build and maintain CI/CD pipelines (Harness or similar), infrastructure-as-code (Terraform), containerization (Docker/Kubernetes), secrets management (Vault/CyberArk) and observability.
•Write reference implementations, templates and starter projects that the rest of the team and AI agents follow.
•Do daily code reviews and pair with engineers, and debug production-grade issues yourself.
Engineering leadership
•Lead the modernization engineering team and set standards for architecture, code quality, testing and release.
•Own technical delivery plans, estimates and release quality, working with Architecture, Platform, Data, QE and the existing application support teams.
•Lead engineering for cutover, parallel runs and handover to run teams.
AI-augmented delivery
•Use AI tools hands-on every day (for example GitHub Copilot, Devin, Blitzy and agent frameworks), and lead from your own experience of what works.
•Build agent workflows, prompt libraries and codebase knowledge context (knowledge graphs, MCP connections to Jira, Confluence, ServiceNow and SharePoint).
•Apply AI to reverse-engineering legacy code, generating specs, converting code and generating tests.
•Track AI productivity and quality (throughput, defect rates, rework, cost per migrated application) and report outcomes to leadership.
Risk, controls and governance
•Put human review checkpoints, audit trails and secure-coding gates on all AI-generated code, in line with State Street technology risk, information security and model governance policies.
•Make sure business logic extracted by AI is checked by subject-matter experts and confirmed through reconciliation before go-live.
People and capability
•Hire, coach and grow a permanent full-stack engineering team, and build AI fluency across the team.
•Manage vendor and temporary capacity and make sure knowledge transfers to permanent staff.
Required experience and skills
•12+ years in software engineering, still actively coding, with 5+ years leading engineering teams on modernization or cloud migration programmes.
•ReactJS: strong in modern React (hooks, TypeScript, Redux or similar), component design, testing (Jest/React Testing Library) and building data-heavy enterprise UIs.
•DevOps: practical experience with CI/CD (Harness, Jenkins or GitHub Actions), Terraform, Docker, Kubernetes/ECS/EKS, Git workflows, automated testing and quality gates.
•AWS: compute, networking, IAM and managed services, and how to design for HA/DR.
•AI: proven hands-on use of AI coding assistants and agents in delivery, with measurable results.
•Comfort reading and reverse-engineering legacy code.
•Experience delivering in a regulated financial services environment.
Preferred
•Knowledge of investment servicing or middle-office areas: trade capture, confirmation, settlement, collateral, reconciliation, investment accounting.
•Experience building MCP servers, knowledge graphs or retrieval-augmented context for engineering agents.
•AWS Professional-level or equivalent certification.
About State Street
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.
