Senior Lead Python Engineer - AI/LLM Risk & Compliance

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in Plano, TX seeks a Senior Lead Software Engineer to join the Chief Technology Office - Risk, Control & Regulatory team.

You will develop Python-based software with data pipelines and secure internal integrations, leveraging LLM agent architectures to deliver trusted risk-focused platforms. You will drive production code, participate in code reviews, build observability, and implement safe-by-default AI patterns while collaborating with Product, Risk, and Data teams to ship

Qualifications

• 5+ years applied software engineering experience.
• Experience with enterprise AI-assisted development tools and security-focused practices.
• Strong Python and SQL skills with production ownership.
• Hands-on API integrations experience (REST/WS) and observability.

Responsibilities

• Drives adoption of AI-assisted engineering practices with secure coding and testing standards.
• Builds and maintains full-stack Python data products powering risk workflows.
• Implements LLM-based services, including RAG, tool orchestration, and guardrails.
• Develops authenticated integrations with internal systems (REST/WS) with strong reliability.
• Contributes to code reviews and builds observable, auditable production systems.
• Collaborates with Product, Risk, and Data teams to refine requirements and deliver iteratively.

Skills

Python

SQL

Data modeling

CI/CD

LLM / AI

System design

Security

Code reviews

API integrations

Leadership

Tools

pytest

Git

Dataclasses

Type hints

CLI frameworks

Job description

JPMorgan Chase & Co. in Plano, TX seeks a Senior Lead Software Engineer to join the Chief Technology Office - Risk, Control & Regulatory team.

You will develop Python-based software with data pipelines and secure internal integrations, leveraging LLM agent architectures to deliver trusted risk-focused platforms. You will drive production code, participate in code reviews, build observability, and implement safe-by-default AI patterns while collaborating with Product, Risk, and Data teams to ship