Lead Software Engineer - Java

JPMorganChase; Mumbai; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

JPMorgan Chase in Mumbai is seeking a Lead Software Engineer to drive design, development, and delivery of secure, scalable financial technology solutions. You will contribute to a fast-paced environment and work across teams to ensure robust software delivery.

As a core technical contributor, you will lead Java microservices, Spring Boot, and AI-assisted tooling, partnering with cross‑functional teams to meet business objectives and drive innovation in a secure manner.

Qualifications

• 5+ years of software engineering experience.
• Strong Java backend microservices with Spring Boot.
• REST/gRPC APIs and OAuth2/JWT security.
• Kafka/MSK experience in production.
• AWS deployment familiarity.
• Docker and Kubernetes basics.
• CI/CD automation and delivery methods.
• SDLC with Agile, resiliency, and security.
• AI-assisted development tools usage and governance.

Responsibilities

• Executes creative software solutions and technical troubleshooting.
• Develops secure production code and reviews peers.
• Improves operational stability by automating remediations.
• Leads evaluation sessions with vendors and teams on architectures.
• Promotes AI-assisted engineering practices with validated outputs.

Skills

Java backend

Spring Boot

REST gRPC

OAuth2 JWT

Kafka MSK

AWS

Docker

Kubernetes

CI/CD

Agile

Job description

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 JPMorgan Chase within the Commercial & Investment Bank, 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, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes‑oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading‑edge technologies
• 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

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Strong Java backend microservices (Java 11/17), Spring Boot, REST/gRPC, security (OAuth2/JWT)
• Java + Spring Boot microservices, solid testing (JUnit/Mockito), performance basics. Kafka/MSK working experience in production
• AWS deployment familiarity + troubleshooting (not necessarily deep networking design)
• Docker + basic Kubernetes usage. Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• In‑depth knowledge of the financial services industry and their IT systems. Practical cloud native experience
• 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