Senior Director of Software Engineering
Join one of the most consequential technology transformations in financial services. At JPMorganChase, you'll have the opportunity to lead a groundbreaking AI engineering program, shaping how the firm modernizes its most critical processing systems. This is a rare chance to build something new — with the resources, talent, and executive support to make it real.
Job Summary
As a Senior Director of Software Engineering at JPMorganChase within Wealth Management Technology, Consumer & Community Banking, you will define and deliver the AI toolchain that accelerates mainframe modernization across Credit, Money Market & Mutual Funds, Statements & Tax, and IBOR domains. You will embed directly with domain subject-matter experts and build agentic systems that ingest legacy code, job schedules, data flows, and production knowledge to produce structured specifications and accelerate migration delivery. This is a hands-on program leadership role: you own the roadmap, manage cross-team governance, and write code alongside your team. You are someone who sees GenAI not as a research exercise but as a practical engineering discipline, turning mainframe complexity into well-specified, verifiable, production-ready modern services.
You thrive in ambiguity, move fast across technical and organizational boundaries, and have the credibility to influence domain leaders, architects, and senior leadership. You have deep proficiency using and extending coding agents and operate mission-critical platforms in production. You will build and manage an AI engineering squad, embed with domain subject-matter experts to capture legacy business logic, and architect multi-agent workflows for code ingestion, specification generation, and automated verification.
Job responsibilities
- Design, build, and operate the end-to-end AI modernization pipeline, including artifact ingestion, specification generation, agent-driven code translation, and automated verification
- Own the strategic sequencing of migration across domains, establishing beachheads, proving the model, and scaling against business commitments and platform readiness
- Build and lead a high-performing AI engineering team, hiring, mentoring, and retaining AI engineers while setting engineering standards and fostering a builder culture
- Partner directly with mainframe subject-matter experts to validate specifications, challenge assumptions, and ensure migrated logic preserves business intent
- Design multi-agent systems for discovery, specification, code generation, and verification, implementing prompt engineering strategies, evaluation frameworks, and guardrails tuned for financial calculation accuracy
- Collaborate with architecture teams to define the target-state platform that all migrated calculations deploy into — deterministic, immutable, and constrained for agent-first development
- Create automated evaluation suites that measure migrated calculations against legacy outputs in simulated and lower environments
- Coordinate with technology leads, architecture teams, vendor partners, and senior leadership, presenting progress, trade-offs, and investment decisions to both technical and executive audiences
- Establish LLMOps practices for the AI toolchain, including deployment, monitoring, cost management, drift detection, and continuous improvement within firm compliance, model risk, and cybersecurity standards
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience; in addition, 5+ years of experience leading technologists to manage, anticipate, and solve complex technical items within your domain of expertise
- Deep hands-on experience building production LLM-based applications, agentic architectures, RAG pipelines, and LLMOps for 24/7 systems
- Distributed systems experience in 24/7 environments, event-driven and batch architectures, API design, and modern cloud platforms (AWS/EKS/ECS/Kafka)
- Demonstrated ability to build and scale engineering teams, including hiring, developing, and retaining senior technical talent
- Expert proficiency with AI-assisted development tools as part of daily engineering workflow
- Excellent communication skills with the ability to translate between highly technical AI concepts and business stakeholder needs
- Experience designing and implementing multi-agent orchestration systems for complex, multi-step workflows
- Proven track record of delivering large-scale technology programs with measurable business outcomes
Preferred qualifications, capabilities, and skills
- Experience in financial services, particularly wealth management, brokerage, or capital markets processing
- Master's degree in Computer Science or equivalent experience
- Familiarity with calculation engines, workflow orchestration, and event sourcing patterns
- Experience with JVM, Rust, PostgreSQL, and Kafka in production environments
- Background in program management for large-scale technology transformations
- Experience building evaluation and verification frameworks for code migration or translation systems