Home/Jobs/Sr Lead Software Engineer - Agentic AI Solutions

Sr Lead Software Engineer - Agentic AI Solutions

JPMorgan Chase

Mumbai

5+ years

Today

$41.0K–55.4K/yr

Full time

Onsite

Skills Required LLM

LangChain

Vector Database

RAG

Prompt Engineering

LangGraph

Context Engineering

A2A

MCP

AutoGen

Python

Pydantic

FastAPI

AWS

EKS

Description JPMorgan Chase is hiring a Sr Lead Software Engineer for its Asset & Wealth Management business. The role focuses on building an AI-native SDLC agent fabric and delivering secure, scalable, multi-agent automation solutions.

Company: JPMorgan Chase

Role: Sr Lead Software Engineer - Agentic AI Solutions

Location: Mumbai, Maharashtra, India

Experience

- 5+ years applied experience
- Experience in software engineering using AI technologies
- Experience with LLM integration, prompt/context engineering, and AI agent frameworks
- Experience deploying end-to-end pipelines on AWS
- Experience with observability and monitoring platforms
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools
- Experience coaching senior engineers and leads on compliant usage patterns and controls

Qualification

- Formal training or certification on software engineering concepts

Responsibilities

- Work closely with software engineers, product managers, and other 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
- Integrate AI agents with toolchains 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
- Improve code quality, delivery speed, and operational outcomes through AI-assisted practices




- Establish measurable validation standards for AI outputs
- Promote reuse of proven patterns and automation within the SDLC/TLM toolchain
- Apply knowledge of software development life cycle toolchain tools to improve automation value at scale

Additional Responsibilities

- Build an AI-native SDLC Agent Fabric and next-generation ecosystem of autonomous, collaborative agents
- Architect, design, and build an intelligent SDLC framework using multi-agent systems, AI toolchains, and LLM orchestration
- Support AI-assisted code review, refactoring, test acceleration, release readiness, and incident/root-cause analysis
- Validate AI outputs for correctness, performance, and security
- Ensure secure handling of inputs and outputs and adherence to resiliency and security expectations

Nice To Have

- Experience with Azure
- Experience with Google Cloud Platform
- Familiarity with MLOps practices
- CI/CD for ML
- model monitoring
- automated deployment
- ML pipelines

More Skills multi-agent orchestration frameworks, Lambda, S3, Terraform, CI/CD, Kubernetes, Docker, APIs, observability, monitoring platforms, Jira, Bitbucket, GitHub, SDK development, data pipelines, secure coding, peer review, automated testing, responsible AI

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