Lead Software Engineer - Terraform, Python, Kubernetes

JPMorgan Chase & Co.; Bengaluru; On-site; INR 4,000,000 - 6,400,000; Full time

Job summary

JPMorgan Chase & Co. in Bengaluru is seeking a Lead Software Engineer to shape secure, scalable technology for Securities Services. You will own end-to-end delivery, drive architecture reviews, and mentor a small team while collaborating with SRE and data science partners.

You will develop Python applications on AWS, implement AIML-enabled solutions, and oversee CI/CD, testing, and production readiness to deliver reliable financial services.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Proven hands-on experience developing, debugging and maintaining production applications.
• Solid understanding of software development best practices, including version control, testing, and CI/CD.
• Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders.
• Experience working on AIML systems and/or prior experience collaborating with data scientists.

Responsibilities

• Develops and maintain high-quality, secure applications using Python and AWS.
• Creates architecture and design deliverables, lead design and architecture reviews, own end-to-end delivery. Integrates AIML solutions into complex, domain specific operations processing systems.
• Leads code reviews, design discussions, and agile planning sessions. Collaborates with SRE and production monitoring teams to ensure system reliability and performance.
• Contributes to software engineering communities of practice and technology events.
• Embraces continuous learning, creative problem solving, and a can-do attitude.
• Leads evaluation and selection of open source and internal software to determine best fit.
• Partners with existing systems teams on cross-app design; align interfaces and ship end-to-end solutions
• Manages small team of engineers whilst remaining hands-on, setting engineering standards
• 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.

Skills

Python

CI/CD

Team leadership

Problem solving

Education

Software engineering cert

Tools

Kubernetes

Docker

Kafka

SageMaker

Bedrock

EKS

Postgres

Job description

Lead Software Engineer - Terraform, Python, Kubernetes

Job Information

• Job Identification 210782437
• Job Category Software Engineering
• Business Unit Commercial & Investment Bank
• Posting Date 10/23/2026, 04:41 AM
• Apply Before 10/27/2026, 04:00 AM
• Job Schedule Full time
• Job Shift Mid-Day

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, Securities Services 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. 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

• Develops and maintain high-quality, secure applications using Python and AWS
• Creates architecture and design deliverables, lead design and architecture reviews, own end-to-end delivery. Integrates AIML solutions into complex, domain specific operations processing systems
• Leads code reviews, design discussions, and agile planning sessions. Collaborates with SRE and production monitoring teams to ensure system reliability and performance
• Contributes to software engineering communities of practice and technology events
• Embraces continuous learning, creative problem solving, and a can-do attitude
• Leads evaluation and selection of open source and internal software to determine best fit
• Partners with existing systems teams on cross-app design; align interfaces and ship end-to-end solutions
• Manages small team of engineers whilst remaining hands-on, setting engineering standards
• 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.
• Proven hands-on experience developing, debugging and maintaining production applications
• Solid understanding of software development best practices, including version control, testing, and CI/CD
• Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
• Experience working on AIML systems and/or prior experience collaborating with data scientists

Track record of designing, building, and delivering maintainable, extensible applications into production environments

Preferred qualifications, capabilities, and skills

• Experience with Cloud services, Infrastructure as Code (IaC) and containerized application development
• Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock
• Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and LLMs
• Experience working on AIML systems and/or prior experience collaborating with data scientists