Lead Software Engineer - Java, Oracle, Kafka, MongoDB

JPMorgan Chase & Co.; Bengaluru; On-site; INR 4,200,000 - 8,000,000; Full time

Job summary

JPMorgan Chase & Co. in Bengaluru seeks a Lead Software Engineer to advance secure, scalable market-leading technology products within Post Trade Technology. You will contribute hands-on coding and guide architectural decisions across a globally distributed team.

Expect strong expertise in Java 11, microservices, AWS, and AI-assisted tooling, with a focus on secure coding, resiliency, and automated testing. The role emphasizes collaboration with stakeholders and delivering high-impact solutions.

Qualifications

• Formal training or certification on software engineering concepts with 5+ years of applied experience
• Hands-on experience delivering system design, development, testing, and operational stability
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Experience with Java 11 and relational databases (Oracle, PostgreSQL) and NoSQL (MongoDB)
• Experience with event-driven development using Kafka and messaging systems (JMS)
• Strong background in microservices across globally distributed teams
• Ability to communicate effectively with technical and non-technical audiences
• Experience with AWS and cloud-native migrations
• Proven use of AI-assisted development tools with focus on validation and security
• Leadership in Communities of Practice for software engineering innovations
• Ability to contribute to coding, reviews, and delivery while aligning with team goals

Responsibilities

• Executes creative software solutions with design, development, and troubleshooting
• Produces secure, high-quality production code and maintains algorithms
• Analyzes large data sets to build visualizations and reports for continuous improvement
• Develops secure production code and reviews others' code
• Identifies data patterns to improve coding hygiene and architecture
• Automates recurring issues to improve operational stability
• Drives adoption of enterprise AI-assisted engineering practices
• Uses SDLC tools to enhance automation and value
• Promotes reuse of effective patterns across teams
• Leads communities of practice to diffuse new technologies

Skills

Agile methodologies

Team collaboration

Communication

Secure coding

Problem solving

Tools

Java 11

Oracle

PostgreSQL

MongoDB

Kafka

JMS

AWS

CI/CD tooling

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's Markets - Post Trade Technology team, 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 breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Advanced coding with Java 11 and advanced capabilities with relational databases such as Oracle, PostgresQL, and Mongo DB
• Experience with event-driven development, Kafka and messaging systems such as Java Messaging System (JMS)
• Strong experience developing applications built on microservices architecture while working across a globally distributed team
• Ability to communicate effectively across different organization levels for technical and non-technical audiences, peers, and leadership teams.
• Experience with AWS ecosystem and application migrations from on-premise and hybrid solutions to fully cloud-native applications
• 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
• Ability to contribute directly to coding, code reviews, and technical team delivery while partnering with management and stakeholders to ensure delivery is aligned with overall team objectives.

Preferred qualifications, capabilities, and skills

• In-depth knowledge of the financial services industry and their IT systems