Lead Software Engineer - Python and AI

Posted Yesterday
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2 Locations
Hybrid
Senior level
Financial Services
We’re one of the world’s biggest technology-driven companies
The Role
Lead design and deliver production-grade agentic AI systems (LLM orchestration, RAG, vector DBs, multi-agent setups). Develop secure, high-quality Python code, drive cloud-native deployments on AWS, CI/CD automation, and platform stability. Mentor teams, promote AI-assisted engineering practices, translate business/regulatory needs into technical designs, and guide adoption of responsible AI and validation standards across cross-functional squads.
Summary Generated by Built In
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. 
As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. 
Job responsibilities
  • Designs and builds production-grade agentic AI systems including LLM orchestration layers, RAG pipelines, vector databases, and MCP-based tool integrations
  • Develops and reviews secure, high-quality code and debugs solutions written by team members or generated by AI models. Architects multi-agent and single-agent setups, authors skill files, and writes technical RFCs for new AI capabilities
  • Contributes to cloud-native deployments (AWS ECS), CI/CD pipelines, and infrastructure modernization alongside platform engineering squads
  • Builds and iterates on agentic patterns — multi-hop agents, vector search, automated code generation — from POC through UAT to full production rollout. Translates regulatory operations and business requirements into precise technical designs and delivers against quarterly commitments
  • Identifies opportunities to automate recurring operational issues, reducing manual toil and improving platform stability. Participates actively in sprint ceremonies, code reviews, and architecture discussions as a senior technical contributor
  • Contributes to an internal developer productivity accelerator as a technical mentor and active builder across 10+ cross-functional teams
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.


Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 5+ years of  applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability. Advanced proficiency in Python; strong object-oriented programming fundamentals
  • Proven experience building and deploying LLM-based or agentic AI systems in production. Deep understanding of RAG architecture, vector databases, and AI agent frameworks (e.g., Lang Graph, MCP)
  • Proficiency in automation and continuous delivery methods (CI/CD, DevOps). Proficient across all phases of the Software Development Life Cycle
  • Advanced understanding of agile methodologies and application resiliency patterns. Practical cloud-native experience on AWS (ECS, Lambda, S3 or equivalent)
  • Strong analytical and problem-solving skills with ability to break down complex technical problems independently
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices


 
Preferred qualifications, capabilities, and skills
 
  • Experience with post-trade financial platforms (e.g., Athena, Quartz, Sec DB)
  • Knowledge of financial services industry IT systems, trade reconciliation,
     and regulatory reporting workflows
  • Experience with AI / ML / Vibe coding and agentic development workflows
  • Knowledge of distributed computing, data modeling, and performance engineering. Familiarity with data lineage, data contracts, and data governance frameworks
  • Experience with ServiceNow, Jira, or Confluence API integrations
  • Regression testing and observability tooling experience in large-scale platforms
 

Skills Required

  • Formal training or certification in software engineering concepts and 5+ years of applied experience
  • Advanced proficiency in Python and strong object-oriented programming fundamentals
  • Proven experience building and deploying LLM-based or agentic AI systems in production
  • Deep understanding of RAG architecture and vector databases
  • Experience with AI agent frameworks (e.g., Lang Graph, MCP) and authoring multi-agent setups
  • Proficiency in automation and continuous delivery methods (CI/CD, DevOps) and SDLC practices
  • Practical cloud-native experience on AWS (ECS, Lambda, S3 or equivalent)
  • Advanced understanding of agile methodologies and application resiliency patterns
  • Demonstrated experience leading use of AI-assisted development tools and setting validation expectations
  • Strong understanding of responsible AI use, data sensitivity, secure handling, and coaching engineers on compliant adoption
  • Experience with post-trade financial platforms (e.g., Athena, Quartz, Sec DB)
  • Knowledge of financial services IT systems, trade reconciliation, and regulatory reporting workflows
  • Experience with AI/ML agentic development workflows and related coding practices
  • Knowledge of distributed computing, data modeling, data lineage, data contracts, and governance frameworks
  • Experience integrating with ServiceNow, Jira, or Confluence APIs
  • Regression testing and observability tooling experience in large-scale platforms

JPMorganChase Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.

  • Healthcare Strength Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
  • Parental & Family Support Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
  • Retirement Support Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.

JPMorganChase Insights

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The Company
HQ: New York, NY
289,097 Employees
Year Founded: 1799

What We Do

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.

Why Work With Us

Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.

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