Lead Software Engineer - Python, AWS, Data, Agentic AI

Job Description

Lead Software Engineer at JPMorgan

Chase within the Corporate Sector – responsible for conducting critical technology solutions across multiple technical areas and supporting firm business objectives.

• Execute creative software solutions, design, develop, and troubleshoot technical issues beyond routine approaches.
• Develop secure, high‑quality production code and review/debug code written by others.
• Identify opportunities to eliminate or automate recurring issues to improve operational stability of software applications and systems.
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability for use within existing systems.
• Lead communities of practice across Software Engineering to promote awareness and use of new technologies.
• Contribute to a team culture of diversity, opportunity, inclusion, and respect.

• Formal training or certification on Software Engineering and application development with 7+ years of applied experience.
• Hands‑on expertise in Python and/or Java with a proven record of delivering secure, high‑quality production code.
• Experience building cloud‑native solutions on AWS (compute, storage, security/IAM, networking, observability).
• Experience with LLMs and agentic systems, including orchestration patterns, tool/function calling, retrieval, structured outputs, evaluations, and safety/guardrails.
• Experience building data‑intensive applications and workflows using Databricks (Spark, Delta, jobs/workflows).
• Proficiency in JavaScript/Type Script and React for building modern web applications.
• Proficiency in automation and continuous delivery methods; strong SDLC discipline (CI/CD, testing, code quality, release controls).
• Advanced understanding of agile delivery, application resiliency, and secure engineering practices.
• Strong system design skills with the ability to make pragmatic trade‑offs and drive alignment across stakeholders.

• Exposure to cloud technologies – AWS EC2, EKS, RDS, S3, Lambdas, EMR, Glue, S3.
• Experience with Big Data technologies such as PySpark, Hadoop, Databricks, ETL, Snowflake.
• Proven experience designing and building data pipelines (ETL/ELT) using modern technologies (Python, SQL, Spark, Airflow, etc.).

Equal Opportunity Employer.