Data Scientist Lead

JPMorgan Chase & Co.; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

JPMorgan Chase & Co. in Bengaluru is seeking a Data Scientist Lead to join its AI engineering team.

You will design and deliver trusted, market-leading AI products and scalable data pipelines on AWS, driving impact across the financial services industry. You will provide technical leadership, mentor engineers, and own end-to-end AI agent integrations, with strong emphasis on secure coding, observability, and delivery speed.

Qualifications

• BE/B.Tech, ME/MS or PhD in Computer Science or Machine Learning field.
• Strong hands-on skills in Python, Pydantic, FastAPI, LangGraph, and Vector Databases for building RAG-based AI agent solutions on AWS.
• Experience with LLM integrations and AI agent frameworks like Langchain/LangGraph/Autogen.
• Deep knowledge in data structures, algorithms, ML, data mining, information retrieval, statistics.
• Expert in NLP, CV, Speech Recognition, RL, ranking/recommendation, or time series analysis.
• Solid understanding of Cloud (AWS/Azure/GCP) and DevOps (CI/CD, Terraform, Kubernetes, Docker, APIs).

Responsibilities

• Designs and implements LLM-driven agent services for design, code generation, documentation, test creation, and observability on AWS.
• Develops orchestration and communication layers between agents using A2A SDK, LangGraph, or Auto Gen.
• Integrates AI agents with 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.
• Drives adoption and governance of AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes; establishes validation standards.
• Applies knowledge of SDLC tools and AI-assisted automation to improve value at scale.

Skills

Python

Pydantic

FastAPI

LangGraph

Vector Databases

LLMs integration

Prompt engineering

Data structures

Algorithms

Machine Learning

Data Mining

Information Retrieval

Statistics

NLP

Computer Vision

Speech Recognition

Reinforcement Learning

Ranking

Time Series Analysis

Cloud (AWS/Azure/GCP)

DevOps

CI/CD

Kubernetes

Docker

Education

BE/B.Tech, ME/MS or PhD in CS or ML field

Tools

Jira

Bitbucket

Github

Terraform

Monitoring platforms

AWS services (EKS, Lambda, S3)

Langchain

LangGraph

Autogen

Job description

As the next push into this investment,JPMC is hiring the best talents to join our AI engineering team. We are executing like a startup and building the next generation technology that combines JPMC unique data and full-service advantage to develop high impact AI applications and platforms in the financial services industry.We are looking for people who are excited about the opportunity.

As a Data Scientist Lead at JPMorgan Chase, you design and deliver trusted market-leading technology products in a secure, stable, and scalable way.

Job Responsibilities

• 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

• BE/B. Tech, ME/MS or PhD degree in Computer Science, or Machine learning related field.


• 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.


• Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining,Information Retrieval, Statistics.


• Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.


• Solid understanding of Cloud (AWS/ Azure/ GCP) and DevOps (CI/CD, Terraform, Kubernetes, Docker and APIs