Lead Software Engineer

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 Data Software Engineer at JPMorgan

Chase within the Commercial and Investment Bank, youare 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.

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect

• Formal training in software engineering concepts and 5+ years of applied experience
• Extensive experience building and operating AWS/public cloud–based applications
• Strong Python (Pyspark) programming skills
• Proven hands‑on delivery across system design, application development, testing, and operational stability.
• Proficiency in automation, CI/CD, and all aspects of the SDLC
• Experience with pipelines and DAGs for data processing and/or machine learning
• Demonstrated proficiency in cloud and AI/ML software practices
• Experience driving adoption of AI engineering tools (e.g., Git Hub Copilot) for JIRA, documentation, coding, and releases, with measurable productivity and quality gains

• AWS (hands-on):
  Glue, Event Bridge, Step Functions, Lambda, ECS, EKS, Kinesis, Cloud Watch
• Outside AWS:
  Python, Terraform, Tiger Graph, graph databases, Git Hub Copilot, Airflow, Kubernetes
• JPMC platforms/tools (highly preferred):
  Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps