Tech Lead (Full Stack), Vice President

State Street

7d•$120,000 - $217,500•Hybrid

About The Position

The Tech Lead (Full Stack), Vice President will lead engineering for a multi-year programme to modernize and migrate a large portfolio of middle-office applications to AWS. The portfolio includes cloud-native rebuilds, like-for-like migrations and application retirements. The role owns engineering delivery and an AI-augmented delivery model that uses AI agents and assistants across discovery, code conversion, testing and deployment, while maintaining the control and quality standards required of a global custodian. The role leads the modernization engineering team, sets standards for cloud-native architecture and delivery, and coordinates technical plans and releases with Architecture, Platform, Data, QE and application support teams. It also leads cutover, parallel runs and handover to run teams. The position designs and operates the programme’s agentic SDLC, selects and orchestrates AI tools based on evidence, builds reusable agent workflows and context, and tracks productivity and quality outcomes. It establishes human review, audit, secure-coding, data-classification and approved-tool controls for AI-assisted work, including validation of extracted business rules with subject-matter experts and reconciliation before go-live. The role hires, coaches and develops a permanent cloud-native engineering team, builds AI fluency, manages vendor and temporary capacity, and transfers knowledge to permanent staff. Success measures include a measured AI-augmented delivery model, modernization releases delivered to plan without material cutover incidents, a permanent team able to operate and evolve the platform, and no audit or control findings related to AI use in delivery. This is a hybrid position requiring a minimum of four days in the office. Stated hours are 8:00 AM to 5:00 PM. The annual salary range is $120,000–$217,500 for the primary location; the range may differ for other work locations. Employees are eligible for a comprehensive benefits program, including retirement savings, insurance coverage, paid time off, an Employee Assistance Program and incentive compensation, subject to applicable eligibility terms.

Requirements

12+ years of experience in software engineering.
5+ years leading large engineering teams on complex modernization or cloud migration programmes.
Strong hands-on background in Java, Spring Boot, microservices, REST, messaging (Kafka or IBM MQ) and AWS, including ECS/EKS, IAM and networking.
Practical experience using AI coding assistants and agents in delivery, with measurable results.
Experience migrating legacy technology stacks, such as COBOL, C/C++, PowerBuilder or Sybase, to modern platforms, including database migration to Oracle.
Working knowledge of CI/CD and DevSecOps (Harness or similar), secrets management (Vault or CyberArk) and observability.
Experience delivering in a regulated financial services environment with strong change and control requirements.
Ability to make decisions and work comfortably with ambiguity.
Credibility in code reviews and with senior stakeholders, and ability to drive adoption of new ways of working while maintaining standards for resilience and trust.

Nice To Haves

Knowledge of investment servicing or middle-office areas, including trade capture, confirmation, settlement, collateral, reconciliation or investment accounting.
Experience building MCP servers, knowledge graphs or retrieval-augmented context for engineering agents.
AWS Professional-level or equivalent certification.

Responsibilities

Lead the engineering team rebuilding critical middle-office applications as cloud-native services on AWS.
Set engineering standards for microservices, event-driven integration using Kafka or MQ, containerization using ECS or EKS, and Oracle data design.
Own technical delivery plans, estimates and release quality in coordination with Architecture, Platform, Data, QE and existing application support teams.
Lead engineering activities for cutover, parallel runs and handover to run teams.
Design and operate the programme’s agentic SDLC, including AI-assisted legacy-code reverse engineering, specification generation, code conversion, test generation and documentation.
Select, combine and orchestrate AI tools and agent frameworks based on evidence of effectiveness.
Build reusable agent workflows, prompt libraries and knowledge context, including codebase knowledge graphs, vector databases and MCP integrations.
Track AI productivity and quality, including throughput, defect rates, rework and cost per migrated application, and report outcomes to leadership.
Establish human-review checkpoints, audit trails and secure-coding gates for AI-generated code in line with technology risk, information security and model governance policies.
Ensure AI-extracted business rules are checked by subject-matter experts and confirmed through reconciliation before go-live.
Manage 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 wider organization.
Manage vendor and temporary capacity, and transfer knowledge to permanent staff.

Benefits

401(k) retirement savings plan with company match.
Insurance coverage including basic life, medical, dental, vision and long-term disability, with other optional additional coverages.
Paid time off including vacation, sick leave, short-term disability and family-care responsibilities.
Access to an Employee Assistance Program.
Incentive compensation, including eligibility for annual performance-based awards, subject to stated exclusions and eligibility.
Eligibility for certain tax-advantaged savings plans.
Inclusive development opportunities.
Flexible work-life support.
Paid volunteer days.
Employee networks.