Sr Lead Software Engineer - Python, Agentic AI Solutions

JPMorgan Chase & Co.; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Sr Lead Software Engineer (Python) for Agentic AI Solutions in Bengaluru. You will join an agile team to design, build, and deliver secure, scalable AI-enabled software across the SDLC, focusing on multi-agent orchestration and AI-driven tooling.

The role requires deep Python expertise and hands-on experience with LLM integration, AI agent frameworks, and AWS deployment. It offers leadership responsibilities and collaboration across product and engineering teams.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years applied experience.
• Experience in Software engineering using AI Technologies.

Responsibilities

• Defines requirements with stakeholders and delivers robust solutions.
• Designs and implements LLM-driven agent services for design, code generation, and observability on AWS.
• Develops orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or Autogen.
• 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 and mentoring to junior engineers.
• Drives adoption and governance of AI-assisted engineering practices across teams to improve quality and speed.
• Applies knowledge of SDLC tools to improve automation and security.

Skills

Python

Pydantic

FastAPI

LangGraph

Vector Databases

LLM integration

CI/CD

Kubernetes

Docker

AWS

Mentorship

Tools

A2A SDK

LangGraph

LangChain

Autogen

Terraform

Jira

Bitbucket

Github

Docker

Job description

Sr Lead Software Engineer - Python, Agentic AI Solutions

Job Information

• Job Identification 210771336
• Job Category Software Engineering
• Business Unit Asset & Wealth Management
• Posting Date 09/10/2026, 03:25 AM
• Locations Parcel 9, Embassy Tech Village, Outer Ring Road, Deverabeesanhalli Village, Varthur Hobli, Bengaluru, IN-KA, 560103, IN
• Apply Before 09/30/2026, 04:00 AM
• Job Schedule Full time
• Job Shift Day

Job Description

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 Sr Lead Software Engineer at JPMorgan Chase within the Asset & Wealth Management, youare 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.

At JPMorgan Chase, we are reimagining software engineering itself – by building an AI-Native SDLC Agent Fabric, a next generated ecosystem of autonomous, collaborative agents that transform every phase of the software delivery lifecycle. We are forming a foundational engineering team to architect, design, and build this intelligent SDLC framework levering multi-agent systems, AI toolchains, LLM Orchestration (A2A, MCP) and innovative automation solutions. If you’re passionate about shaping the future of engineering—not just building better tools, but developing a dynamic, self-optimizing ecosystem—this is the place for you.

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.

Required qualifications, capabilities, and skills

• Formal training or certification onsoftware engineeringconcepts 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.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.

Preferred qualifications, capabilities, and skills

• Experience with Azure or Google Cloud Platform (GCP).
• Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.