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# Senior Lead Software and Data Engineer - Agentic Commerce

- **Company:** JPMorgan Chase & Co.
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Agile Methodology, Artificial Intelligence, Continuous Integration, Software Debugging, Distributed Systems, Graph Database, Python (Programming Language), Software Engineering, Software Systems, Toolchain, Large Language Models, Multi-Agent Systems, AI Coding Agents, Agentic-AI, Kubernetes, Information Technology, Production Code, Machine Learning Operations, Model Registry, Graph RAG, Databricks, Programming Languages, Agent2Agent Protocol
- **Published:** October 2, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210795856

## About the Role

* Demonstrate formal training or certification in software engineering concepts with advanced applied experience
 * Apply hands-on experience in system design, application development, testing, and operational stability
 * Show advanced proficiency in one or more programming languages, with Python required
 * Architect and ship production LLM agents or multi-agent systems
 * Design end-to-end ML platforms or MLOps pipelines
 * Exhibit expertise in secure distributed systems, including identity, authorization, and service-to-service trust
 * Lead with AI-assisted software development tools and validate AI outputs
 * Understand responsible AI use, data sensitivity, and secure engineering workflows
 * Demonstrate proficiency in all aspects of the Software Development Life Cycle
 * Apply advanced understanding of agile methodologies such as CI/CD, application resiliency, and security
 * Display in-depth knowledge of financial services industry IT systems

Preferred Qualifications, Capabilities, and Skills:

 * Deep experience with agent protocols and frameworks such as MCP, A2A, AG-UI, Google ADK, or LangGraph
 * Experience with agent payment and mandate patterns, or regulated workflows requiring auditable LLM output
 * Experience with OpenFGA or OPA/Rego, service mesh technologies, and micro-VM isolation
 * Experience with Databricks, MLflow, and model serving on Kubernetes, including GPU capacity planning and small language model inference
 * Experience with knowledge graphs, GraphRAG, or organizational memory for agents
 * Experience with optimization, pricing, or negotiation models in production
 * Domain knowledge of B2B payments, commercial card, supplier enablement, or treasury

## Description

* Set technical direction and reference architecture for B2B agentic commerce, including multi-agent topology and agent-to-agent communication
 * Design information barriers and authorization for agents acting on behalf of different counterparties, ensuring secure and isolated execution
 * Define MLOps architecture for agent tools, covering training, environment promotion, model registry, serving, monitoring, and retraining cadence
 * Establish engineering standards for agent quality and safety, including evaluation frameworks, guardrails, and model risk approval evidence
 * Execute creative software solutions, design, development, and technical troubleshooting beyond conventional approaches
 * Develop secure, high-quality production code and review/debug code written by others
 * Partner with platform, product, risk, and client-facing teams to integrate external agents and contribute reusable capabilities
 * Drive adoption of enterprise-authorized AI-assisted engineering practices, establishing validation standards and promoting reuse
 * Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development and automation
 * Identify opportunities to eliminate or automate remediation of recurring issues for operational stability
 * Lead evaluation sessions with vendors and internal teams to assess architectural designs and technical credentials


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