JPMorgan Chase & Co.
Context Plane Python Engineer
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Join a greenfield engineering effort at the heart of JPMorganChase's AI strategy. As part of the Corporate Technology Data and Analytics Services organization, you'll help build a platform that is redefining how AI agents and large language model tools access governed, trusted firm knowledge. This is a rare opportunity to shape architecture from the ground up, work alongside a small, senior team, and grow your expertise at the intersection of data engineering and applied AI — with full support to learn the graph and AI stack on the job.
As a Lead Software Engineer at JPMorganChase within the Data Core Engineering group, you will design and build the Context Plane — a platform that connects the data mesh and other knowledge sources to the AI agents and tools that consume firm context. You will own components end-to-end, from ingestion pipelines that load firm knowledge into graph and vector stores, to the serving layer that retrieves and returns governed, provenance-tagged context to downstream agents. Because this platform is early-stage, your engineering decisions will have lasting impact on how it evolves.
Job Responsibilities
- Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store, ensuring reliability, security, and scalability
- Build and evolve the serving layer — including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint that agents call for context
- Extract and promote reusable components into a shared core library, reducing duplication and improving consistency across the platform's repositories
- Integrate with data sources and services across the firm, including AI and large language model gateways, to enable governed and traceable context delivery
- Own quality across your components through automated testing, code reviews, observability instrumentation, and resilient service design
- Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into working, measurable platform capabilities
- Contribute to design discussions and agile ceremonies, bringing pragmatic engineering instincts and a bias toward practical, scalable solutions
- 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
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Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Demonstrated proficiency in Python, with hands-on experience building production-grade backend services and data pipelines
- Strong grasp of API design principles (e.g., FastAPI or equivalent frameworks), automated testing, CI/CD practices, and source control workflows
- Experience building and operating containerized services on cloud infrastructure (e.g., AWS, Docker, ECS)
- Ability to own components end-to-end — from design through deployment and observability — with a pragmatic, outcome-focused engineering approach
- Demonstrated ability to collaborate cross-functionally with product, data science, and platform engineering teams to deliver working capabilities
- 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
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
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Preferred Qualifications, Capabilities, and Skills
- Experience with graph databases and query languages (e.g., Neo4j, Cypher), or a strong interest in graph data modeling and knowledge graph design
- Familiarity with vector search, embeddings, or retrieval-augmented generation (RAG) patterns
- Exposure to large language model serving platforms (e.g., Bedrock, Azure OpenAI) or agentic patterns such as tool/function calling and Model Context Protocol
- Experience with Databricks, MongoDB, or large-scale data integration and ETL workflows
- Knowledge of data governance, data lineage, and entitlements concepts in an enterprise data environment
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
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.
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
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