Software Engineer III- Python AWS AI Enablement

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III- Python / AWS / AI Enablement at JPMorganChase within the Asset & Wealth Management Technology team you will design and build scalable services and platforms that power investment and wealth solutions. You will work hands-on across application code and cloud infrastructure delivering reliable secure and well-observed systems. Youll collaborate closely with product engineering data/AI partners and control functions to enable modern AI capabilities (including MCP and AI tooling integrations) while maintaining high standards for engineering excellence and operational stability.

Job Responsibilities

• Design develop test and deploy Python-based microservices APIs and data-driven applications supporting AWM business workflows and platforms.
• Build and operate cloud-native solutions on AWS (or equivalent cloud platforms) focusing on scalability resiliency performance and cost awareness.
• Implement MCP (Model Context Protocol) and integrate AI tools to enable safe consistent and reusable model/application interactions and developer workflows.
• Develop and maintain infrastructure and automation using infrastructure-as-code and CI/CD practices.
• Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality delivery speed and productivity across complex deliverables (e.g. code generation/refactoring unit test creation documentation) while validating outputs through peer review automated testing and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Apply 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.
• Collaborate with cross-functional teams to define technical requirements design patterns and service interfaces; participate in architecture and code reviews.
• Establish strong observability practices (logging metrics tracing) drive incident response readiness and continuously improve operational excellence.
• Contribute to secure engineering practices (authentication/authorization patterns secrets management dependency hygiene and SDLC controls).
• Mentor junior engineers and contribute to a culture of inclusion ownership and continuous improvement.

Required Qualifications Capabilities and Skills

• Formal training or certification on software engineering concepts and 3 years applied experience
• Python development experience (building production services/applications).
• Hands-on experience with AWS or another major cloud platform (designing deploying and operating cloud workloads).
• Working knowledge of MCP (Model Context Protocol) and experience using AI tools to build or integrate AI-enabled features/workflows.
• Strong software engineering fundamentals: data structures APIs testing reliability performance tuning and code quality practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g. for coding test creation troubleshooting or documentation) with demonstrated ability to critically evaluate validate and refine AI-generated outputs for correctness performance and security.
• Understanding of responsible AI use in engineering workflows including data sensitivity considerations secure handling of inputs/outputs and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
• Experience with CI/CD pipelines and modern delivery practices (e.g. automated testing artifact/version management release strategies).
• Strong communication skills and ability to partner effectively across engineering product and control stakeholders.

Preferred Qualifications Capabilities and Skills

• Java coding experience (e.g. maintaining or integrating with JVM-based services).
• Exposure to front-end development and React (e.g. building small UI components supporting full-stack delivery).
• Experience with containers and orchestration (e.g. Docker Kubernetes/EKS) and/or serverless patterns.
• Familiarity with observability tooling and practices (metrics distributed tracing SLOs/SLIs).