Senior Lead Software Engineer, AI-Driven Risk Tech

JPMorgan Chase & Co.

Plano (TX)

On-site

USD 150,000 - 190,000

Full time

2 days ago

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Job summary

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

You will develop Python-based software combining data pipelines, internal-system integrations, and AI/LLM capabilities, delivering secure, scalable, production-quality solutions. You will lead the full stack effort, drive governance of AI practices, and collaborate with Product, Risk, Controls, Compliance, and data teams to deliver high-impact,

Qualifications

Formal training or certification on software engineering concepts and 5+ years applied experience.
Experience leading enterprise AI-assisted software development tools within the work environment with ability to validate AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling, resiliency and security expectations.
Strong hands-on system design and application development skills with production ownership (delivery, stability, incident response).
Advanced Python proficiency (3.10+), including dataclasses, type hints, generators/streaming, CLI frameworks, and clean package structure.
Strong SQL and data-modeling skills: correct, performant, read-only queries across large schemas.
Hands-on experience delivering generative AI/LLM solutions (RAG, tool orchestration, guardrails).
Proven experience building authenticated API integrations (REST/WebSocket) with robust error handling.
Experience building secure, auditable systems (versioning, access controls, logging, monitoring).
Data-engineering pragmatism: streaming large files, ETL on real-world data.
Experience building production Python with modern CI/CD practices (pytest, linting, git/PR).

Responsibilities

Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality and delivery outcomes.
Build and maintain the full-stack Python toolkit and data products for agentic risk-oversight workflows.
Implement LLM-based services, including RAG, tool orchestration, and evaluation/guardrails.
Develop authenticated integrations and APIs to internal systems (REST and streaming/WebSocket) with secure auth and scaling.
Work on data pipelines with Data Scientists; join large datasets using read-only SQL across wide schemas.
Write secure, high-quality production code and comprehensive tests; participate in code reviews.
Build observability into services (logs/metrics/tracing) and assist in incident response.
Implement safe-by-default patterns for AI features with audits and human-in-the-loop when appropriate.
Generate audience-ready outputs, including interactive HTML dashboards and evidence packages.
Collaborate with Product/Risk/Controls/Compliance/data teams to refine requirements.
Utilize enterprise AI tools responsibly to accelerate delivery while validating outputs.