Lead Software Engineer - Java Fullstack, AWS

Lead Software Engineer - Java Fullstack, AWS

Mumbai, Maharashtra, India

Job Information

• Job Identification 210784396
• Job Category Software Engineering
• Business Unit Commercial & Investment Bank
• Posting Date 09/30/2026, 04:17 AM
• Locations 6TH & 7TH FLRS,WINGA & 6TH 7TH,8TH, & 9TH FLRS, WING B,PARADIGM TOWERS, , MINDSPACE L.RD,MALAD(W), Mumbai, IN-MH, 400064, IN
• Apply Before 10/23/2026, 12:00 AM
• Job Schedule Full time

Job Description Be an integral part of an agile team that continually pushes the envelope to enhance, build, and deliver high-quality technology products.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Banking and Reconciliation team, you will play a critical role in designing, building, and delivering secure, stable, and scalable solutions. You will bring deep expertise in Java full-stack engineering, system design, and software architecture, and you will be expected to drive end-to-end deliveries—from requirements and architecture through build, test, release, and production support.

Job Responsibilities

• Lead end-to-end delivery of complex initiatives: translate business outcomes into technical designs, plan execution, drive delivery milestones, and ensure production readiness.
• Provide technical guidance and direction to business and technical teams, including contractors and vendors.
• Build secure, high-quality production code (Java full stack) and conduct thorough code reviews; debug and uplift code written by others.
• Own system design and architecture decisions: define service boundaries, APIs/contracts, data models, resiliency patterns, scalability strategies, and non-functional requirements (performance, security, availability).
• Drive decisions that influence product design, application functionality, and technical operations/processes (CI/CD, observability, incident response, reliability).
• Serve as a function-wide subject matter expert in one or more focus areas (e.g., Java microservices, cloud-native architecture, distributed systems, AWS).
• Actively contribute to the engineering community as an advocate of firmwide frameworks, tools, and SDLC best practices.
• Influence peers and project decision-makers to adopt leading-edge technologies and modern engineering patterns.
• 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
• Advanced hands-on experience in Java with strong grasp of backend engineering fundamentals (concurrency, performance, security, testing).
• Proven ability to deliver system design, application development, testing, and operational stability in production environments.
• Demonstrated strength in design and architecture: microservices and distributed systems patterns, event-driven architecture, API design, data consistency, resiliency and fault tolerance.
• Ability to tackle design and functionality problems independently with little to no oversight; comfortable acting as the engineering “driver” to unblock delivery.
• Practical cloud-native experience, including building, deploying, and operating services on cloud platforms.
• Strong ownership mindset with the ability to drive quality across the SDLC: design reviews, implementation, automation, release, and ongoing support.
• 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 in AWS (e.g., designing/deploying cloud-native services, security and IAM concepts, monitoring/observability, cost-aware design).

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