Sr Lead Software Engineer - Agentic AI Solutions

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Asset and Wealth Management, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Works closely with software engineers, product managers, and other stakeholders to define requirements and deliver robust solutions.

• Designs and Implement LLM-driven agent services for design, code generation, documentation, test creation and observability on AWS

• Develops orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or Auto Gen

• Integrates AI agents with toolchains such as Jira, Bitbucket, Github, Terraform and monitoring platforms

• Collaborates on system design, SDK development and data pipelines supporting agent intelligence

• Provides technical leadership, mentorship, and guidance to junior engineers and team members.

• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

-
Drives decisions that influence the product design, application functionality, and technical operations and processes

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years 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 integrating with multi-agent orchestration frameworks and deploying end-to-end pipelines on AWS (EKS, Lambda, S3, Terraform)