Sr Lead Software Engineer - Agentic AI

JPMorgan Chase Bank; Bengaluru; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

JPMorgan Chase Bank in Bengaluru is seeking a Senior Lead Software Engineer to push the envelope in AI-native software delivery. You will be a core technical contributor, building trusted, scalable products and mentoring peers across teams.

You will design LLM-driven agent services, orchestrate multi-agent frameworks, and integrate with Jira, GitHub, Terraform, and AWS to improve quality, speed, and reliability of engineering outcomes.

Qualifications

• 5+ years of software engineering experience with AI technologies.
• Hands-on skills with Python, FastAPI, LangGraph and vector databases.
• Experience deploying end-to-end AI pipelines on AWS (EKS, Lambda, S3).
• Strong knowledge of CI/CD, Kubernetes, Docker and APIs.
• Experience with LLM integration and multi-agent orchestration tools.
• Ability to coach and mentor junior engineers and leads.

Responsibilities

• Collaborate with engineers and product managers to define requirements.
• Design and implement LLM-driven agent services for AI projects.
• Develop orchestration layers between agents using LangGraph, Autogen, MCPs, A2A.
• Integrate AI agents with Jira, Bitbucket, Github, Terraform and monitoring tools.
• Contribute to system design, SDK development and data pipelines.
• Provide technical leadership and governance of AI-assisted practices.

Skills

AI Technologies

Python

FastAPI

LangGraph

Vector Databases

LLM integration

CI/CD

Kubernetes

Docker

AWS

Code review

Mentorship

Education

Software engineering certification

Tools

Jira

Bitbucket

Github

Terraform

EKS

Lambda

S3

A2A SDK

LangGraph

Autogen

MCPs

A2A

Job description

Be an integral part of an agile team thats 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, 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.

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 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.
• 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.