We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will work on challenging Cloud-native data, backend engineering and AIML engineering, helping us industrialize AI/ML models at Production scale. This role is a technical hands-on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- 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.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps
- Designs and implements data engineering solutions, leveraging modern big data technologies
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages- Python
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- 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.
- Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications
- Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies
- Practical experience developing Production-scale Cloud-native data engineering solutions in commercial environments
- Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack
- Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds and Overall knowledge of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
- Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector
- Experience working on LLM applications or other AI/ML systems
- Practical experience with Kubernetes, EKS, Docker, MLOps
- Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases
- Prior experience collaborating with data scientists
Skills Required
- Formal training or certification in software engineering concepts and 5+ years of applied experience
- Hands-on experience in system design, application development, testing, and operational stability
- Proficiency coding in Python
- Experience developing, debugging, and maintaining code in a large corporate environment
- Experience leading the effective use of enterprise-authorized AI-assisted software development tools
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security expectations
- Experience coaching senior engineers or leads on compliant AI-assisted engineering usage
- Experience designing, architecting, and developing microservices, distributed systems, and data-intensive applications
- Experience with cloud services, Infrastructure as Code, containerized application development, big data, and modern data engineering technologies
- Practical experience developing production-scale cloud-native data engineering solutions in commercial environments
- Familiarity with cloud data engineering services such as ETL, Glue, S3, and Athena, plus an MLOps stack
- Ability to communicate design choices and results clearly to stakeholders from varied backgrounds
- Overall knowledge of the Software Development Life Cycle
- Experience with data, AWS, and AI/ML engineering in commercial settings, preferably in the financial sector
- Experience working on LLM applications or other AI/ML systems
- Practical experience with Kubernetes, EKS, Docker, and MLOps
- Exposure to LLMs, RAG, knowledge graph technologies, OpenSearch, and vector databases
- Prior experience collaborating with data scientists
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
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Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
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Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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