Senior Lead Software Engineer - Python and AI/ML

As a Senior Lead Software Engineer at JPMorgan Chase within the Asset & Wealth Management team, you have the opportunity to impact your career and be part of an agile team that works on enhancing, building, and delivering market-leading technology products. You will play a vital role in conducting critical technology solutions across various business functions to support the firms objectives. JPMorgan Chase is reimagining software engineering by developing an AI-Native SDLC Agent Fabric, an ecosystem of autonomous agents that transform the software delivery lifecycle. If you are passionate about shaping the future of engineering and developing a self-optimizing ecosystem, this is the place for you. Key Responsibilities: - Work closely with software engineers, product managers, and stakeholders to define requirements and deliver robust solutions. - Design and implement LLM-driven agent services for design, code generation, documentation, test creation, and observability on AWS. - Develop orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or Auto Gen. - Integrate AI agents with toolchains such as Jira, Bitbucket, Github, Terraform, and monitoring platforms. - Collaborate on system design, SDK development, and data pipelines supporting agent intelligence. - Provide technical leadership, mentorship, and guidance to junior engineers and team members. - Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes. - Apply knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation at scale. Qualifications Required: - Formal training or certification on software engineering concepts and 5+ years of applied experience. - Experience in software engineering using AI technologies. - Strong hands-on skills in Python, Pydantic, FastAPI, LangGraph, and Vector Databases for building RAG based AI agent solutions. - Solid understanding of CI/CD, Terraform, Kubernetes, Docker, and APIs. - Familiarity with observability and monitoring platforms. - Strong analytical and problem-solving mindset. - Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment. - Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs/outputs. This job requires experience with LLMs integration, prompt/context engineering, AI Agent frameworks like Langchain/LangGraph, Autogen, MCPs, A2A. Familiarity with Azure or Google Cloud Platform (GCP) and experience with MLOps practices are preferred for this Senior Level position at JPMorgan Chase. As a Senior Lead Software Engineer at JPMorgan Chase within the Asset & Wealth Management team, you have the opportunity to impact your career and be part of an agile team that works on enhancing, building, and delivering market-leading technology products. You will play a vital role in conducting critical technology solutions across various business functions to support the firms objectives. JPMorgan Chase is reimagining software engineering by developing an AI-Native SDLC Agent Fabric, an ecosystem of autonomous agents that transform the software delivery lifecycle. If you are passionate about shaping the future of engineering and developing a self-optimizing ecosystem, this is the place for you. Key Responsibilities: - Work closely with software engineers, product managers, and stakeholders to define requirements and deliver robust solutions. - Design and implement LLM-driven agent services for design, code generation, documentation, test creation, and observability on AWS. - Develop orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or Auto Gen. - Integrate AI agents with toolchains such as Jira, Bitbucket, Github, Terraform, and monitoring platforms. - Collaborate on system design, SDK development, and data pipelines supporting agent intelligence. - Provide technical leadership, mentorship, and guidance to junior engineers and team members. - Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes. - Apply knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation at scale. Qualifications Required: - Formal training or certification on software engineering concepts and 5+ years of applied experience. - Experience in software engineering using AI technologies. - Strong hands-on skills in Python, Pydantic, FastAPI, LangGraph, and Vector Databases for building RAG based AI agent solutions. - Solid understanding of CI/CD, Terraform, Kubernetes, Docker, and APIs. - Familiarity with observability and monitoring platforms. - Strong analytical and