Senior Lead Software Engineer, Technology Risk

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Plano, TX
Posted: 23 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $198k

$138k most similar roles pay here $245k

This listing doesn't post a salary. Most similar roles pay $171,750–$223,750.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Senior Lead Software Engineer, Technology Risk

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As a Senior Lead Software Engineer - Technology Risk within the Chief Technology Office - Risk, Control & Regulatory team, you will join an agile team focused on building and delivering secure, stable, and scalable technology products. You will develop Python-based software featuring data pipelines, authenticated internal-system integrations, and generative AI/LLM-based agent capabilities. Your daily work involves building a full-stack Python toolkit for risk-oversight workflows, implementing RAG, tool orchestration, and prompt management on a PostgreSQL platform. You will manage complex API integrations using REST and WebSocket protocols while ensuring security compliance through robust authentication and observability. Key technical requirements include advanced Python proficiency, performant SQL for large schemas, and experience with CI/CD practices. The role addresses critical risk management domains by creating automated tools to navigate data sensitivity, ensure responsible AI usage, and provide evidence packages for risk stakeholders.

Skills

Python PostgreSQL LLM RAG REST WebSocket SQL CI/CD Pytest HTML CSS Chart.js Spark Databricks SDLC Data-engineering System Design

What you'll do

Build and maintain full-stack Python toolkits and data products for agentic risk-oversight workflows.
Implement LLM-based services including RAG, tool calling, agent orchestration, and guardrails.
Develop authenticated REST and streaming API integrations with robust security and error handling.
Construct data pipelines to stream, normalize, and join large datasets using performant SQL.
Write secure production code and comprehensive tests while conducting rigorous peer code reviews.
Build observability into services through logs, metrics, and tracing to automate remediation of operational issues.
Drive the adoption of AI-assisted engineering practices to improve code quality and delivery speed.
Create audience-ready outputs such as interactive HTML dashboards for technical and non-technical stakeholders.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Demonstrated experience leading the use of enterprise-authorized AI-assisted development tools for coding, review, and troubleshooting.
Strong understanding of responsible AI usage, including data sensitivity, secure handling, and coaching others on compliant patterns.
Advanced Python proficiency (3.10+) using dataclasses, type hints, generators, and CLI frameworks.
Strong SQL and data modeling skills to perform queries across large schemas with high performance.
Hands-on experience delivering generative AI/LLM solutions including RAG, tool orchestration, evaluation, and guardrails.
Experience building authenticated API integrations (REST and streaming) with robust error handling and security protocols.
Experience building secure, auditable systems and production Python using modern CI/CD practices.
Experience with risk management domains in regulated environments (preferred).
Experience authoring LLM agent systems and knowledge-base/RAG design (preferred).
Frontend-lite reporting skills for generating interactive HTML dashboards (preferred).
Exposure to distributed computing or cloud data platforms (preferred).

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