Lead Software Engineer - Java and AI/ML

JPMorganChase; Mumbai; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer in Mumbai to join the Global Banking technology team. You will be a core technical contributor delivering trusted, market-leading products with scalable microservices, Spring Boot APIs, and secure coding practices.

You will drive AI-assisted engineering adoption, automate workflows, and ensure high quality through testing and integrated tooling. You will contribute to design, development, and operations across multiple business functions,

Qualifications

• Advanced Java development experience with strong fundamentals (OO design, concurrency, performance)
• Experience with Spring Boot and REST APIs, security, persistence; Elastic search
• Hands-on experience using Copilot/Claude Code for delivery acceleration
• Experience building AI agents/LLM-enabled workflows with grounding/verification
• Some Python scripting for automation/AI prototyping
• Knowledge of CI/CD, resiliency, and security in Agile environments
• Practical experience with Kubernetes
• Experience leading use of AI-assisted development tools with validation of outputs

Responsibilities

• Executes creative software solutions, design, development, and debugging of complex problems
• Develops secure production code (Java/Spring Boot) and reviews peers' code
• Leads design and delivery of scalable microservices/APIs in the Spring ecosystem
• Improves engineering productivity with AI4Tech practices and code modernization
• Builds and operationalizes AI agents integrating with engineering workflows
• Uses Python for AI prototyping and automation
• Promotes diversity, inclusion, and responsible AI use in engineering
• Drives adoption of enterprise AI-assisted development and automation tools

Skills

Java development

Spring Boot

AI2Tech tools

AI agents/LLM workflows

Python scripting

CI/CD

Kubernetes

Secure coding

Tools

Elastic Search

Job description

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

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 JPMorganChase within the Commercial & Investment Bank- Global Banking, 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

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code (primarily Java / Spring Boot), and reviews and debugs code written by others
• Leads the design and delivery of scalable microservices/APIs within the Spring ecosystem (e.g., Spring MVC/WebFlux, Spring Data, Spring Security), with strong testing practices
• Proactively improves engineering productivity using AI4Tech practices, including hands‑on use of Copilot/Claude Code for refactoring, test generation, documentation, and code modernization—while ensuring correctness and secure coding standards
• Builds and operationalizes AI agents that integrate with engineering workflows (e.g., PR review assistants, runbook/support agents, remediation assistants), including tool/function calling, structured outputs, and safety/guardrails
• Uses Python as needed for AI/agent prototyping, automation, evaluation harnesses, or glue code/integrations
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required Qualifications, Capabilities, And Skills

• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced Java development experience with strong fundamentals (OO design, concurrency, performance, debugging)
• Strong hands‑on experience with Spring Boot and related frameworks (REST APIs, security, persistence), Elastic search, plus unit/integration testing.
• AI4Tech hands‑on experience using Copilot/Claude Code (or similar approved tools) to accelerate delivery while maintaining code quality, security, and test coverage
• Experience building AI agents / LLM-enabled workflows, including prompt discipline, grounding/verification strategies, and safe handling of sensitive data
• Some experience or working knowledge of Python (scripting, automation, or AI/agent prototyping)
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Practical experience on Kubernetes
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (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 engineers on safe, compliant adoption within delivery practices

Preferred Qualifications, Capabilities, And Skills

• Experience designing and operating production‑grade agentic systems (observability, evals, prompt/versioning, fallbacks, rate limits, and guardrails)
• Experience with modern microservice patterns (resiliency, distributed tracing, event‑driven design)

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