Applied AI ML Lead - Machine Learning Engineer - Agentic Commerce

JPMorgan Chase & Co.
London, UK
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

JavaScript (Programming Language) Artificial Intelligence Amazon Web Services Confluence Microsoft Azure Computer Programming Continuous Delivery Data Mining Data Structures Graph Database Information Retrieval Python (Programming Language)
+30 more
PostgreSQL Machine Learning NoSQL Systems Development Life Cycle Redis Svelte Next.js Search Technologies SQL Databases TypeScript Real Time Systems Retrieval-Augmented Generation Transfer Learning Large Language Models Snowflake Multi-Agent Systems Agentic-AI Kubernetes Information Technology Data Analytics Bitbucket Data Management Machine Learning Operations Graph RAG Splunk Network Server OpenSearch AWS EKS Databricks Agent2Agent Protocol

Job description

As a Lead AI and ML Engineer in Digital & Platform Services / Data Analytics, you will design, productionize, and operate LLM-powered Agentic Commerce B2B agents on NEO. You will apply MLOps for automation, continuous delivery, and compliance, turning innovative ideas into shipped, production-grade agents. You’ll partner closely with business, product, data science, and engineering teams, expanding NEO’s portfolio of production agents across CIB sub-LOBs and Payments. Your work will help drive secure, auditable, and impactful AI solutions., * Design and ship production agents on NEO, owning them from prototype through production

  • Build robust retrieval systems using Graph RAG, knowledge-graph traversal, vector search, chunking, ranking, and grounding strategies
  • Design agent memory, including episodic and semantic memory nodes, recall, summarization, and decay policies
  • Manage organizational context, assembling entitlement-, lineage-, and tenant-aware context for secure agent reasoning
  • Compose multi-agent workflows using A2A and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk)
  • Build and run task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, and quality/safety gating
  • Deploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC, security, resiliency, and observability practices
  • Partner with product and business teams to turn use cases into shipped, supported agents
  • Build traditional ML model training pipelines and productionize them using MLOps best practices
  • Develop batch and online inference for ML models

Requirements

  • MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience)
  • Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails
  • Strong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics
  • Knowledge of Kubernetes (AWS EKS)
  • Experience with training models in Databricks and SageMaker
  • Experience working with MLFlow
  • Practical RAG experience-retrieval quality, embeddings, and vector stores; Graph RAG a strong plus
  • Expert knowledge of at least one of: AWS, Azure, Kubernetes
  • Knowledge of data management and data model design; real-time processing using SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis)
  • Excellent communication skills with the ability to partner effectively with senior technical and business stakeholders, * Experience with agent frameworks or runtimes, A2A, or MCP
  • Agent memory design (memory nodes, episodic/semantic memory) and organizational context management
  • Knowledge graphs and graph databases used for retrieval
  • Understanding of LLM fine-tuning and small language model inference
  • Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK)
  • Experience working in the financial or payments domain at a large institution

About the company

Join us to shape the future of AI-powered solutions at JPMorganChase. You’ll leverage the firm’s scale, data, and technology to deliver measurable impact across the Commercial & Investment Bank and Payments. As a Lead AI and ML Engineer, you’ll collaborate with talented teams in a fast-paced environment, building agents that real businesses depend on. We offer opportunities for career growth, exposure to cutting-edge platforms, and the chance to make a difference in a regulated, secure setting., 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., J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

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Apply on jpmc.fa.oraclecloud.com
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