Senior Lead Software Engineer - Java, Kafka, Cloud

JPMorganChase; Mumbai; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

JPMorganChase in Mumbai seeks a Senior Lead Software Engineer to join Payments Technology. You will guide multi-team efforts, develop secure production code, and drive AI-assisted practices to improve code quality, delivery speed, and operational reliability.

Responsibilities include setting team expectations for AI outputs, contributing to enterprise frameworks, and shaping design decisions while ensuring resilience and security across services.

Qualifications

• Proven expertise in building large scale & high throughput application.
• Proficient in Java, Spring Boot, Kafka & cloud native applications.
• Demonstrated experience using enterprise AI-assisted software development tools to improve code quality.
• Strong understanding of securing AI outputs, governance, and resiliency in engineering workflows.

Responsibilities

• Provides technical guidance to business and technical teams, contractors and vendors.
• Develops secure, high-quality production code; reviews and debugs others' code.
• Drives AI-assisted engineering practices to improve code quality, delivery speed, and operations with measurable validation standards.

Skills

Java

Spring Boot

Kafka

Cloud-native

Distributed systems

Performance analysis

AI-assisted development tools

Independent problem solving

Tools

Kubernetes

APIGEE gateway

Cloud services

Job description

Job Description

Be an integral part of an agile team that constantly pushes the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Payments Technology, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required Qualifications, Capabilities, And Skills

• Proven expertise in building large scale & high throughput application
• Proficient in Java, Spring Boot, Kafka & cloud native applications
• Proficient in distributed systems and parallel processing
• Proficient in Performance Analysis and Tuning (Working knowledge of Java based Profiling and Monitoring Tools)
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
• Ability to tackle design and functionality problems independently with little to no oversight

Preferred Qualifications, Capabilities, And Skills

• Working experience of Kafka Streams, Even Driven Architecture, Microservices Architecture
• Good understanding of Behavior driven design
• Understanding of Kubernetes, APIGEE gateway and cloud services
• Working knowledge of agentic workflows
• Proven production deliverables in agentic AI
• Hands-on across the modern AI toolchain