Tech Lead (Full Stack), Vice President

State Street•Quincy, MA

6d•Hybrid

About The Position

The Tech Lead (Full Stack), Vice President will lead engineering delivery 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 applies 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 engineering teams rebuilding critical middle-office applications as cloud-native services on AWS, establishes engineering standards, and owns technical plans, estimates, and release quality. It also designs and operates agentic software-development workflows, measures their productivity and quality, and ensures human review, auditability, secure coding, proper data classification, and approved-tool use. The position hires and develops a permanent cloud-native engineering team, builds AI fluency, manages vendor and temporary capacity, and transfers knowledge to permanent staff. The position is hybrid, with a minimum of four days in the office, and has working hours of 8:00 AM to 5:00 PM. The stated annual salary range is $120,000–$217,500, with the applicable range potentially differing for employees working outside the specified location. State Street describes its benefits program as including retirement savings, insurance coverage, paid time off, an Employee Assistance Program, incentive compensation eligibility, and certain tax-advantaged savings plans.

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/IBM MQ), and AWS (ECS/EKS, IAM, networking).
Practical experience using AI coding assistants and agents in delivery, with measurable results.
Experience migrating legacy 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/CyberArk), and observability.
Experience delivering in a regulated financial services environment with strong change and control requirements.

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 modernization engineering team rebuilding 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 in collaboration 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 reviewed 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 wider organization.
Manage vendor and temporary capacity and transfer knowledge to permanent staff.

Benefits

Retirement savings plan (401K) with company match.
Insurance coverage including basic life, medical, dental, vision, long-term disability, and 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, except for certain sales roles subject to sales incentive plans.
Eligibility for certain tax-advantaged savings plans.
Inclusive development opportunities.
Flexible work-life support.
Paid volunteer days.
Employee networks.