Senior Lead AI Engineer — Python & Risk

Socket.dev; Plano (TX); On-site; USD 180,000 - 250,000; Full time

Job summary

JPMorganChase, within the Chief Technology Office - Risk, Control & Regulatory, seeks a Senior Lead Software Engineer to drive the Python data platform, AI-enabled services, and secure integrations in a fast-moving, risk-aware environment.

You will own production-grade code, partner with data scientists, build observability, and ensure compliance with security standards while delivering scalable risk-management tooling for internal customers.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Strong hands-on system design and production ownership with delivery, stability, and incident response.
• Advanced Python (3.10+), idiomatic dataclasses and type hints are required.
• Hands-on experience with generative AI/LLM solutions, including RAG and tool orchestration.
• Proven ability to build authenticated API integrations (REST/WS) with robust error handling.

Responsibilities

• Drives adoption and governance of AI-assisted engineering practices across teams.
• Build and maintain the full-stack Python toolkit and data products powering risk workflows.
• Develop LLM-based services, including retrieval-augmented generation and tool orchestration.
• Create authenticated integrations to internal systems with secure auth and reliable performance.
• Build observability, troubleshoot production issues, and automate remediation.

Skills

Advanced Python

SQL & data modeling

Generative AI/LLM

REST & WebSocket APIs

CI/CD & testing

Education

Formal software engineering training

Tools

PostgreSQL

Python tooling

Dataclasses & type hints

CI/CD tooling

Job description

JPMorganChase, within the Chief Technology Office - Risk, Control & Regulatory, seeks a Senior Lead Software Engineer to drive the Python data platform, AI-enabled services, and secure integrations in a fast-moving, risk-aware environment.

You will own production-grade code, partner with data scientists, build observability, and ensure compliance with security standards while delivering scalable risk-management tooling for internal customers.