Tech Lead — AI-Driven Cloud Modernization (Full Stack)

State Street Corporation; England; Hybrid; GBP 90,000 - 163,000; Full time

Job summary

State Street Corporation in the United Kingdom leads a multi-year program to modernize middle-office applications on AWS, delivering cloud-native services with AI-augmented workflows. You will own engineering delivery and the AI-enabled SDLC, guiding architecture, platform and data teams through complex cutovers and secure coding practices.

You will build a permanent cloud-native engineering team, manage vendor capacity, and ensure regulatory compliance with rigorous change controls across the

Qualifications

• 12+ years in software engineering, with 5+ years leading large engineering teams on 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++, PowerBuilder, Sybase) to modern platforms, including database migration to Oracle.
• Working knowledge of CI/CD and DevSecOps (Harness or similar), secrets management (Vault/CyberArk) and observability.
• Experience delivering in a regulated financial services environment with strong change and control requirements.

Responsibilities

• 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.
• 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 GitHub 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.
• 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.
• 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.
• 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.
• An AI-augmented delivery model running across the programme, with productivity gains measured against a baseline.

Skills

Java/Spring Boot

Microservices

REST

Kafka/IBM MQ

AWS

AI tools

CI/CD

Security

Tools

Harness

Vault

CyberArk

Job description

State Street Corporation in the United Kingdom leads a multi-year program to modernize middle-office applications on AWS, delivering cloud-native services with AI-augmented workflows. You will own engineering delivery and the AI-enabled SDLC, guiding architecture, platform and data teams through complex cutovers and secure coding practices.

You will build a permanent cloud-native engineering team, manage vendor capacity, and ensure regulatory compliance with rigorous change controls across the