Overview: Join JPMorganChase in Glasgow, United Kingdom as a Senior Lead Software Engineer to help build 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 architectural decisions will shape the platform.

Responsibilities

Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store
Build and evolve the serving layer — including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agents
Extract and promote reusable components into a shared core library to reduce duplication
Integrate with data sources and services across the firm, including enterprise AI and LLM gateways
Own quality across your components: automated testing, code reviews, observability, and secure, resilient service design
Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into measurable capabilities
Mentor teammates and contribute to design discussions and agile ceremonies
Promote enterprise-approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, including secure coding standards and automated testing
Apply SDLC toolchain knowledge, including AI-assisted

Responsibilities

Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store
Build and evolve the serving layer — including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agents
Extract and promote reusable components into a shared core library to reduce duplication
Integrate with data sources and services across the firm, including enterprise AI and LLM gateways
Own quality across your components: automated testing, code reviews, observability, and secure, resilient service design
Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into measurable capabilities
Mentor teammates and contribute to design discussions and agile ceremonies
Promote enterprise-approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, including secure coding standards and automated testing
Apply SDLC toolchain knowledge, including AI-assisted

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