JP Morgan Chase

Runs a consumer bank and an investment bank

Lead Software Engineer - Multiple Teams

Backend EngineeringConfirmed live in the last 24 hours

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.
Extensive experience building and running applications based on AWS or public cloud.
Strong programming skills in Python.
Hands-on experience delivering system design, application development, testing, and operational stability.
Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle.
Experience with pipelines and directed acyclic graphs for processing data and/or machine learning.
Proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, or machine learning.
In-depth knowledge of the financial services industry and its IT systems.
Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, and setting team 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 resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.

Responsibilities

Execute software solutions through design, development, and technical troubleshooting, using creative approaches to build solutions and break down technical problems.
Develop secure, high-quality production code, and review and debug code written by others.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish validation standards for secure coding, peer review, and automated testing; and promote reuse of effective patterns across the team.
Apply Software Development Life Cycle toolchain capabilities, including authorized AI-assisted development and automation, to improve the value realized from automation.
Identify opportunities to eliminate or automate remediation of recurring issues to improve the operational stability of software applications and systems.
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability within existing systems and information architecture.

Desired Qualifications

Experience with cloud services, Infrastructure as Code, and containerized application development.
Familiarity with relational databases such as Postgres and AWS services such as S3, EKS, SageMaker, and Bedrock.
Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, and Large Language Model Operations.
Experience working on artificial intelligence and machine learning systems and/or prior collaboration 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

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
Develops secure and high-quality production code, and reviews and debugs code written by others
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 evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience.
Extensive experience in building and running AWS/public cloud based applications
Solid programming skills with Python
Hands-on practical experience delivering system design, application development, testing, and operational stability
Proficiency in automation and continuous delivery methods and all aspects of the Software Development Life Cycle
Experience of pipelines and DAG's (Directed Acyclic graph) for processing data and/or machine learning
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence and machine learning.)
In-depth knowledge of the financial services industry and their IT system.
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 Large Language Model Operations (LLMOps)
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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