Lead Software Engineer - Java

JPMorgan Chase & Co.; Mumbai; On-site; INR 4,200,000 - 7,600,000; Full time

Job summary

JPMorganChase in Mumbai seeks a Lead Software Engineer to contribute as a core technical member of an agile team. You will build, secure, and scale market-leading technology products across multiple business functions to support the firm’s objectives.

You will guide design, development, testing, and deployment, promote AI-assisted practices, and ensure secure, resilient software delivery while collaborating with vendors and internal stakeholders.

Qualifications

• Formal training or certification in software engineering concepts.
• 5+ years of applied software engineering experience.
• Strong backend Java development experience.

Responsibilities

• Develops secure production code and reviews code written by others.
• Drives architectural discussions with internal teams and external vendors.
• Promotes AI-assisted engineering practices and secure coding standards.
• Leads communities of practice and drives adoption of new technologies.

Skills

Java

Spring Boot

REST/gRPC

OAuth2/JWT

CI/CD

Agile methodologies

AI-assisted engineering

Cloud native

Code reviews

Education

Software engineering training/certification

Tools

Kubernetes

Docker

Kafka

AWS

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 JPMorganChase 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