Lead Full Stack Engineer - Assistant Vice President
Hands-on engineering lead at State Street in Bangalore driving a multi-year AWS modernization of middle-office applications: building ReactJS/TypeScript/NodeJS front ends, DevOps pipelines and infrastructure-as-code, while running an AI-augmented delivery model using coding agents and assistants.
- Compensation
- Not disclosed
- Location
- Bangalore, India
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Full time
- Experience
- 5+ years
- Category
- Fullstack
- Posted
Skills
Must have
- 12+ years in software engineering, still actively coding
- 5+ years leading engineering teams on modernization or cloud migration programmes
- Strong modern React (hooks, TypeScript, Redux or similar)
- Component design, testing (Jest/React Testing Library), data-heavy enterprise UIs
- Practical DevOps experience: 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, design for HA/DR
- 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
Nice to have
- 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
Full description
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.