Lead Software Engineer - AI ML
at J.P. Morgan
Posted 17 days ago
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Lead Software Engineer at JPMorgan Chase within Asset & Wealth Management to architect and build an AI-native SDLC Agent Fabric. Responsible for designing and implementing LLM-driven agent services, multi-agent orchestration, and integrations with toolchains and AWS (EKS, Lambda, S3, Terraform). Provides technical leadership and mentorship while delivering production-grade RAG-based AI agent solutions, CI/CD, and observability capabilities.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Asset & 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. 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
- 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.
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)
- Experience with LLMs integration, prompt/context engineering, AI Agent frameworks like Langchain/LangGraph, Autogen, MCPs, A2A.
- Solid understanding of CI/CD, Terraform, Kubernetes, Docker and APIs
- Familiarity with observability and monitoring platforms
- Strong analytical and problem-solving mindset.
- Experience with Azure or Google Cloud Platform (GCP).
- Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.
