Are you a senior Python engineer who wants to work at the intersection of data platforms and applied AI? This is your opportunity to join a small, high-impact team building something new from the ground up — where your decisions shape the architecture, not just the backlog. At JPMorganChase, we invest in engineers who are curious, pragmatic, and ready to grow into emerging technology stacks.As a Senior Lead Software Engineer at JPMorganChase within the Corporate Technology Data and Analytics Services team, you will be a founding contributor to the Context Plane — a greenfield platform that connects the firm's data mesh and knowledge sources to AI agents and large language model tools. You will own components end-to-end, from ingestion pipelines to governed retrieval services, and your engineering instincts will directly influence how the platform evolves. This is a hands-on senior role with real architectural scope, active cross-functional collaboration, and strong support for internal mobility and upskilling.Job responsibilitiesDesign, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector storeBuild and evolve the serving layer — including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agentsExtract and promote reusable components into a shared core library, reducing duplication across the platform's repositoriesIntegrate with data sources and services across the firm, including enterprise AI and large language model gatewaysOwn quality across your components: automated testing, code reviews, observability, and resilient, secure service designPartner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into working, measurable capabilitiesContribute to design discussions and agile ceremonies, and actively mentor teammates to raise the engineering bar across the teamDrives 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 teamApplies 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 automationRequired qualifications, capabilities, and skillsFormal training or certification on software engineering concepts and advanced applied experienceDemonstrated expertise building production-grade backend services and data pipelines in PythonStrong command of API design principles (e.g., FastAPI), automated testing, CI/CD practices, and source control workflowsExperience designing and building data ingestion or integration pipelines at scale, with attention to data quality and resilienceProficiency working with cloud infrastructure (AWS) and containerized services (Docker/ECS)Ability to own technical components end-to-end — from design through deployment and observabilityStrong collaboration skills with the ability to work across engineering, product, and data science disciplinesHands-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 securityUnderstanding 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 practicesPreferred qualifications, capabilities, and skillsExperience with graph databases and Cypher query language (e.g., Neo4j) or a strong interest in graph data modelingFamiliarity with vector search, embeddings, or retrieval-augmented generation (RAG) patternsExposure to large language model serving, agentic patterns (tool/function calling, Model Context Protocol), or platforms such as Bedrock or Azure OpenAIExperience with Databricks, MongoDB, or large-scale extract, transform, and load / data integration workflowsKnowledge of data governance, lineage, and entitlements concepts in an enterprise environmentJ.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.Full timePosting Date: 2026-07-24