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The Role
Build and ship production AI-enabled software, primarily backend services in Python. Develop APIs, microservices, LLM-driven agentic workflows, SQL-backed business logic, and inference integrations. Support CI/CD, containers, Kubernetes, Terraform, multi-cloud infrastructure, observability, incident response, and secure production operations. Collaborate across the software development lifecycle while using and validating enterprise-authorized AI coding tools.
Summary Generated by Built In
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 JPMorganChase within the AI/ML Technology, you will be a hands-on engineer responsible for building and shipping production software with a strong focus on AI-enabled capabilities. You will work across the full software development lifecycle—from requirements clarification and design through implementation, testing, deployment, and production support. You will develop backend services in Python, build APIs and micro-services, implement LLM-based solutions including agentic workflows, and deliver into a multi-cloud environment using Terraform, Kubernetes, and CI/CD pipelines. This role offers you the opportunity to grow your expertise in applied AI engineering while contributing to systems that operate at enterprise scale.
Job responsibilities
As a Lead Software Engineer at JPMorganChase within the AI/ML Technology, you will be a hands-on engineer responsible for building and shipping production software with a strong focus on AI-enabled capabilities. You will work across the full software development lifecycle—from requirements clarification and design through implementation, testing, deployment, and production support. You will develop backend services in Python, build APIs and micro-services, implement LLM-based solutions including agentic workflows, and deliver into a multi-cloud environment using Terraform, Kubernetes, and CI/CD pipelines. This role offers you the opportunity to grow your expertise in applied AI engineering while contributing to systems that operate at enterprise scale.
Job responsibilities
- Deliver software through a disciplined software development lifecycle, working from well-defined requirements through design, implementation, testing, release, and production support
- Write maintainable Python code with unit and integration tests, debugging issues across application, API, data-access, and runtime layers
- Implement LLM-driven workflows including prompting, tool and function calling, routing, orchestration, and state handling to support multi-step agentic task execution
- Build and maintain inference-time integrations such as model gateways, APIs, caching, fallbacks, timeouts, and concurrency controls for production AI systems
- Build REST and gRPC endpoints following agreed contracts, implementing authentication and authorisation integration, input validation, error handling, and secure data handling practices
- Implement SQL-backed business logic powering APIs and micro-services, including joins, aggregations, filtering, pagination, and transactional workflows
- Contribute to CI/CD pipelines and Git workflows, packaging and deploying services using containers and Kubernetes with support for safe rollouts and rollbacks
- Contribute to infrastructure-as-code using Terraform within established team patterns across modules, environments, and state management
Improve operability of services by adding and using observability tooling including logs, metrics, traces, dashboards, and alerts, and participate in incident response and root-cause analysis - Leverage enterprise-authorised AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorised AI-assisted development and automation capabilities, to improve the value realised by automation
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and proficient applied experience
- Strong hands-on JavaScript, Java or Python development experience building backend services, including testing, packaging, dependency management, and maintainability
- Strong database and SQL proficiency, with experience implementing application logic and APIs on top of relational data
- Experience building APIs and micro-services using REST or gRPC, including contracts, security basics, and observability
- Practical experience delivering LLM-based features as part of software systems, with familiarity with agentic patterns
- Working knowledge of delivery and operations including CI/CD, and Git
- Familiarity with Kubernetes and cloud infrastructure concepts in a multi-cloud environment
- Solid understanding of software engineering fundamentals and software development lifecycle practices including design, reviews, testing, release, and production support
- Hands-on experience using enterprise-authorised AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
- Strong experience with container orchestration platforms (Kubernetes distributions such as EKS, AKS, GKE or OpenShift, or managed equivalents such as ECS or Azure Container Apps), and with the cloud infrastructure that supports them.
- Experience with relational and/or NoSQL databases in the cloud (e.g. RDS/Aurora, DynamoDB, Azure SQL/Cosmos DB, GCP Cloud SQL/Firestore, Oracle).
Preferred skills
- Familiarity with Terraform and cloud infrastructure concepts in a multi-cloud environment
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
- Strong debugging and troubleshooting skills in distributed systems, including root-cause analysis and performance bottleneck identification using logs, metrics, and traces
- Experience improving code quality and reliability through test strategy improvements, refactoring, static analysis, and dependency hygiene
- Experience with deployment and operational best practices including safe releases, rollbacks, environment configuration, and incident readiness
- Familiarity with common architecture patterns such as event-driven designs, async processing, caching, API versioning, and backward compatibility
- Experience collaborating effectively in agile delivery, including estimating, breaking down work, documenting decisions, and communicating risks
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Skills Required
- Formal training or certification in software engineering concepts with proficient applied experience
- Strong hands-on JavaScript, Java, or Python development experience building backend services
- Strong database and SQL proficiency with relational data
- Experience building REST or gRPC APIs and microservices
- Practical experience delivering LLM-based features and familiarity with agentic patterns
- Working knowledge of CI/CD and Git
- Familiarity with Kubernetes and cloud infrastructure in a multi-cloud environment
- Understanding of software engineering fundamentals and the software development lifecycle
- Hands-on experience using enterprise-authorized AI-assisted software development tools and validating generated outputs
- Strong experience with Kubernetes distributions or managed container orchestration platforms and supporting cloud infrastructure
- Experience with relational and/or NoSQL databases in the cloud
- Familiarity with Terraform and multi-cloud infrastructure concepts
- Understanding of responsible AI use, data sensitivity, secure handling, resiliency, and security expectations
- Strong debugging and troubleshooting experience in distributed systems using logs, metrics, and traces
- Experience improving code quality through testing, refactoring, static analysis, and dependency hygiene
- Experience with deployment practices including safe releases, rollbacks, configuration, and incident readiness
- Familiarity with event-driven architecture, asynchronous processing, caching, API versioning, and backward compatibility
- Experience collaborating in agile delivery, including estimation, work breakdown, documentation, and risk communication
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.
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The Company
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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