JP Morgan Chase

Runs a consumer bank and an investment bank

Lead Software Engineer

Backend EngineeringPosted on Nov 12

Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Hands-on experience in Python application development.
Hands-on experience developing, debugging, and maintaining production applications.
Understanding of software development best practices, including version control, testing, and continuous integration and continuous delivery (CI/CD).
Experience working on artificial intelligence and machine learning (AI/ML) systems and/or collaborating with data scientists.
A track record of designing, building, and delivering maintainable, extensible applications into production environments.
Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, and setting expectations for validating AI outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.

Responsibilities

Develop and maintain high-quality, secure applications using Python and AWS.
Create architecture and design deliverables, lead design and architecture reviews, and own end-to-end delivery.
Integrate AI/ML solutions into complex, domain-specific operations processing systems.
Lead code reviews, design discussions, and agile planning sessions.
Collaborate with site reliability engineering (SRE) and production monitoring teams to ensure system reliability and performance.
Contribute to software engineering communities of practice and technology events.
Lead evaluation and selection of open-source and internal software to determine the best fit.
Partner with existing systems teams on cross-application design, align interfaces, and deliver end-to-end solutions.
Manage a small team of engineers while remaining hands-on and setting engineering standards.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish validation standards, including secure coding, peer review, and automated testing, and promote reuse of effective patterns across the team.
Apply knowledge of software development life cycle (SDLC) tools, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Desired Qualifications

Experience with cloud services, infrastructure as code (IaC), and containerized application development.
Familiarity with relational databases such as PostgreSQL and AWS services such as S3, EKS, SageMaker, and Bedrock.
Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, and large language models (LLMs).
Experience working on AI/ML systems and/or collaborating with data scientists.

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 in Python application development
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
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 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

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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