If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.
JP Morgan Chase’s ambitions for AI/ML are transformational, but safety and security are non negotiable. As a Principal Software Engineer within AI Governance Engineering, you will design and build platforms and shared services that enable teams to develop, deploy, and operate AI/ML solutions with compliance and governance seamlessly integrated. Your focus will be to deliver best in class developer tooling that reduces friction and operational toil while raising the firmwide standard for security, reliability, auditability, and responsible AI.
This role is suited to a Senior Engineer who can operate as a technical leader across multiple teams—defining architecture, influencing standards, and delivering high impact software that scales.
Job Responsibilities
Architect and build governance-by-design platforms that embed policy controls, approvals, and evidence collection into the AI/ML delivery lifecycle (from development to validation to deployment and monitoring)
Develop reusable services and APIs that enable consistent governance capabilities across diverse AI/ML use cases (e.g., model onboarding, registration, metadata capture, lineage, and lifecycle state management)
Create developer-first tooling (CLI, SDKs, libraries, templates, automated checks) that makes compliant workflows the easiest workflows
Integrate controls into CI/CD pipelines for ML systems, including automated validation gates, artifact integrity checks, and promotion workflows with audit trails
Design secure-by-default patterns for sensitive data handling and model operations, collaborating with security partners to meet firm standards
Implement observability and monitoring for governance platforms, including operational telemetry, usage analytics, and control effectiveness measurement
Drive engineering excellence through design reviews, reference architectures, coding standards, performance benchmarking, and reliability engineering practices
Partner with stakeholders across engineering, model risk, compliance, legal, privacy, and business teams to translate governance requirements into scalable technical solutions
Mentor and grow engineers, providing technical guidance and fostering a culture of quality, ownership, and continuous improvement
Contribute to strategic roadmap for AI governance engineering, identifying opportunities to reduce toil, automate controls, and improve time-to-market safely
Required Qualifications, Capabilities, and Skills:
Professional software engineering experience with ownership of complex, production-grade systems
Proficiency in programming languages such as Python, Java, C++, Go, or Scala
Understanding of AI/ML concepts and lifecycle fundamentals, including model evaluation, drift, reproducibility, and feature pipelines
Experience designing and operating distributed systems or internal platforms used by multiple teams
Strong technical communication and stakeholder management skills
Preferred Qualifications, Capabilities, and Skills:
Experience delivering systems with auditability, traceability, and compliance requirements in regulated environments
Ability to influence architecture decisions and collaborate effectively across teams