Lead Software Engineer AI + Python
JPMorgan Chase · Posted Nov 6
Global banking, investment, credit card, mortgage, and asset management services
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About the role
JPMorganChase Corporate Technology is building GenAI applications and agentic AI platforms for Finance use cases, leveraging firmwide AI tools and platforms. The role leads architecture and hands-on implementation of cloud-native AWS services and reusable platform capabilities such as agents, retrieval/RAG, guardrails, tool orchestration, and APIs, with strong evaluation, observability, reliability, security, and cost controls. The engineer mentors senior engineers and drives cross-team architecture standards in a regulated enterprise environment.
What you will do
- Lead the architecture and hands-on delivery of scalable, reliable agentic AI platforms for enterprise workflows
- 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.
- Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration. Architect retrieval and context-engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management
- Engineer cloud-native AI services on AWS using containers and serverless patterns, event-driven messaging, and distributed data stores. Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls
- Build well-governed APIs and integrations that connect AI capabilities to enterprise platforms, tools, and business processes
- Establish evaluation, experimentation, regression testing, and observability frameworks to continuously improve quality and agent behavior
- Mentor senior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
Skills used in this role
What the employer is looking for
- Formal training or certification on software engineering concepts and 8+ years applied experience
- Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns
- 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
- Familiarity with agentic workflows and frameworks (e.g., LangChain, LangGraph, Autogen, CrewAI and A2A etc). Experience building retrieval-augmented generation solutions (embeddings, semantic search, grounding) using Vector databases and managing prompt lifecycle/versioning
- Strong software engineering fundamentals with ability to deliver cloud-native services using containers and serverless designs on AWS. Advanced python programming skills with experience writing production quality code
- Build systems using frontier models from OpenAI, Anthropic or others leveraging platforms such as AWS Bedrock / Google Vertex AI or other similar platforms
- Proven technical leadership skills, including mentoring, driving architecture decisions, and influencing cross-functional stakeholders
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Preferred qualifications
- Experience building standardized evaluation harnesses, automated regression suites, and experimentation platforms for large language model systems
- Hands-on experience with Kubernetes-based deployment patterns and operational excellence practices for high-availability services
- Experience applying privacy, data minimization, and safe AI guardrail patterns in regulated or high-risk environments
- Familiarity with context-efficiency optimization techniques and cost governance for large language model workloads. Experience building reusable developer platforms, reference architectures, and technical standards across multiple teams
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
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