Lead Software Engineer Python AWS

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As a Lead Software Engineer Python AWS at JPMorgan Chase within the Corporate Technology, 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

• Design, Develop and implement software solutions.
• Solve business problems through innovation and engineering practices.
• Engage in the full Software Development Life Cycle (SDLC), from requirements analysis through design, development, testing, and deployment.
• Incorporate architectural standards into application design specifications, translating technical requirements into programmed application modules, and developing and enhancing software application modules.
• Identify and troubleshooting application code-related issues.
• Take active role in code reviews to ensure solutions are aligned to predefined architectural specifications.
• Assist with Design reviews by recommending ways to incorporate requirements into designs and data flows.
• Perform development and DevOps in a distributed environment.
• 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 applied experience
• Experience building Microservices using python, Docker, Jenkins, Python-Streamlit, SQL, JSON, Kubernetes, AWS EMR, AWS EC2, AWS RDBMS (Postgres, Oracle) , Apache Spark, Pyspark, Tensorflow
• Application architecture disciplines and technical design for financial applications.
• Experienced with pair programming agents such as GitHub Copilot to accelerate prototyping.
• 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
• Solid grasp of Agile SDLC, CI/CD, and security best practices
• Experience developing in large-scale corporate environments
• Excellent problem-solving skills and the ability to think critically and creatively
• Experience in mentoring and guiding junior engineers

Preferred qualifications, capabilities, and skills

• AWS Certified Solutions Architect certification
• Experience in MLOps and building model serving applications
• Experience with Agentic AI architecture and agents to solve business challenges
• Experience in observability and production management tools (ex. Splunk / Dynatrace / Grafana)​
• Utilize AI agents and emerging technologies to build prototypes for demonstration purposes, presenting to peer groups, business partners, and senior leadership.
• Define standards, best practices, and governance guidelines for the ML Platform.