Tech Lead; Full Stack), Vice President

You’ll lead engineering on a multi-year programme to modernize and migrate a large portfolio of middle-office applications to AWS. The portfolio covers cloud-native rebuilds, like-for-like migrations and retirements. You’ll own engineering delivery and the AI-augmented delivery model: using AI agents and assistants across discovery, code conversion, testing and deployment to cut cost and time. You’ll keep the control and quality standards a global custodian needs.

• Engineering leadership
• Lead the modernization engineering team that rebuilds critical middle office applications as cloud-native services on AWS.
• Set engineering standards for microservices, event-driven integration (Kafka/MQ), containerization (ECS/EKS) and Oracle data design.
• Own technical delivery plans, estimates and release quality, working with Architecture, Platform, Data, QE and the existing application support teams.
• Lead the engineering side of cutover, parallel runs and handover to run teams.
• AI-augmented delivery
• Design and run the programme's agentic SDLC: AI-assisted reverse engineering of legacy code, spec generation, code conversion, test generation and documentation.
• Choose, combine and orchestrate AI tools (for example Git Hub Copilot, Devin, Blitzy and agent frameworks) based on evidence of what works, not tool preference.
• Build reusable agent workflows, prompt libraries and knowledge context (codebase knowledge graphs, vector databases, MCP integrations).
• 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 rules extracted by AI are checked by subject-matter experts and confirmed through reconciliation before go-live.
• Handle data classification and approved-tool usage for client and confidential data.
• People and capability
• Hire, coach and grow a permanent cloud-native engineering team, and build AI fluency across the team and the wider organization.
• Manage vendor and temporary capacity, and transfer knowledge to permanent staff.

• 12+ years in software engineering, with 5+ years leading large engineering teams on complex modernization or cloud migration programmes.
• Strong hands-on background in Java/Spring Boot, microservices, REST and messaging (Kafka/IBM MQ) and AWS (ECS/EKS, IAM, networking).
• Proven, practical experience using AI coding assistants and agents in delivery, with measurable results.
• Experience migrating legacy stacks (e.g. COBOL, C/C++, Power Builder, Sybase) to modern platforms, including database migration to Oracle.
• Working knowledge of CI/CD and Dev Sec Ops  (Harness or similar), secrets management (Vault/Cyber Ark) and observability.
• Experience delivering in a regulated financial services environment with strong change and control requirements.

• 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.

• 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 engineering team in place, able to run and evolve the new cloud-native platform.
• No audit or control findings related to how AI is used…