About this role
Join a dynamic team where your expertise shapes innovative AI products and advances technology solutions. Experience career growth and make a meaningful impact through your contributions.
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading Agentic AI products in a secure, stable, and scalable way. You drive significant business impact through your capabilities and contributions, applying deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. We value your leadership, technical guidance, and commitment to excellence as you help shape the future of our engineering community.
Job responsibilities
- Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develop secure and high-quality production code, and review and debug code written by others
- 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.
- Drive decisions that influence product design, application functionality, and technical operations and processes
- Serve as a function-wide subject matter expert in one or more areas of focus
- Contribute to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Required qualifications, capabilities and skills
- Formal training or certification on software engineering concepts and 8+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced skills in one or more programming languages (Java, Python, Golang)
- Advanced knowledge on building AI agents and hands-on experience with one or more Agentic AI frameworks including tool calling, memory, guardrails, and policy enforcement
- Understanding of Model Context Protocol (MCP) concepts and ecosystem
- Strong knowledge on relational and NoSQL databases (PostgreSQL, DynamoDB, MongoDB)
- 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.
- Ability to tackle design and functionality problems independently with little to no oversight
- Practical cloud native experience on AWS with experience in developing highly resilient, low-latency web services architecture
Preferred qualifications, capabilities and skills
- Well versed with MCP specification and ecosystem
- Proficiency with ElasticSearch / Opensearch
- Agentic controls involving Sandboxing, Identity, and security