Lead Software Engineer - Python, Data, Cloud, AIML
JPMorgan Chase · Posted Oct 6
Global banking, investment, credit card, mortgage, and asset management services
Get a personal compatibility score
Add a resume for personal matches
About the role
The Commercial & Investment Bank's Markets Research Technology team delivers trusted market-leading technology products in a secure, stable, and scalable way, supporting critical technology solutions across business functions. The work spans Cloud-native data, backend engineering, and AIML engineering to industrialize AI/ML models at production scale. This hands-on Lead Software Engineer role designs, builds, and troubleshoots software solutions, including data engineering, backend systems, Cloud infra DevOps, and MLOps.
What you will do
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps
- Designs and implements data engineering solutions, leveraging modern big data technologies
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.
Skills used in this role
What the employer is looking for
- Formal training or certification on software engineering concepts and and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages- Python
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications
- Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies
- Practical experience developing Production-scale Cloud-native data engineering solutions in commercial environments
- Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack
- Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds and Overall knowledge of the Software Development Life Cycle
Preferred qualifications
- Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector
- Experience working on LLM applications or other AI/ML systems
- Practical experience with Kubernetes, EKS, Docker, MLOps
- Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases
- Prior experience collaborating with data scientists
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
Recent coverage
GuruFocus
JPMorgan Chase CEO Warns of AI Cybersecurity Risks as JPM Retains Top AI Bank Ranking2026-10-06
Zacks Investment Research
JPMorgan Chase & Co. (JPM) Reports Next Week: Wall Street Expects Earnings Growth2026-10-06
JPMorgan Chase Newsroom
Ford Motor Company, JPMorganChase, State of Michigan, Michigan Central and Newlab launch Michigan LIFT2026-09-29
JPMorgan Chase Newsroom
JPMorganChase expands DFW presence with new Collin County office2026-08-27
JPMorgan Chase Newsroom
JPMorganChase doubles down on housing, aiming to deploy $750 billion through 20352026-08-03