Role purpose This is a hands-on role for a Senior 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 the full stack but will be primarily responsible for Backend (Java back ends, DevOps, CI/CD pipelines). You'll also set up and run the programme'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 full-stack engineering • Design and write production code for cloud-native services and user interfaces, especially for the most complex or highest-risk components. • Build Java/Spring Boot microservices and APIs (REST and Kafka/MQ event-driven), with Oracle persistence on ECS/EKS. • Build and maintain CI/CD pipelines (Harness or similar), infrastructure-as-code (Terraform), containerization (Docker/Kubernetes), secrets management (Vault/CyberArk) and observability. • Some knowledge of ReactJS/Typescript • 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, vector databases, MCP integrations). • 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. • Java: expert in Java 17+, Spring Boot, JPA, REST API design, Kafka/IBM MQ messaging and performance tuning. • 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. • Databases: strong SQL; experience with Oracle and with migrating from Sybase or SQL Server. • AI: proven hands-on use of AI coding assistants and agents in delivery, with measurable results. • Comfort reading and reverse-engineering legacy code (COBOL, C/C++, PowerBuilder). • 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. Success measures (first 12–18 months) • Personally delivered production code and reference implementations across the front end, back end and pipelines. • An AI-augmented delivery model running across the programme, with productivity gains measured against a baseline. • Modernization releases delivered to plan, with no material production incidents at cutover. • A permanent full-stack team in place, able to run and evolve the new platform. • No audit or control findings related to how AI is used in delivery. Leadership attributes You make decisions and are comfortable with ambiguity. You're equally credible writing code, reviewing a pull request or presenting to senior stakeholders. You set the technical bar by example. 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. 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. 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