Applied AI ML Lead - Machine Learning Engineer - Agentic Commerce

JPMorgan Chase & Co.; City of Westminster; On-site; GBP 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in London seeks a Lead AI and ML Engineer to design, productionize, and operate LLM-powered agents on the NEO platform. You will implement MLOps, automation, and compliance to ship production-grade agents.

You will partner with business, product, data science, and engineering teams to scale the agent portfolio across CIB sub-LOBs and Payments, delivering secure, auditable AI solutions.

Qualifications

• Design and ship production agents from prototype to production.
• Hands-on experience building LLM-powered or agentic applications in production.
• Strong programming skills in Python with knowledge of ML fundamentals.
• Experience with Kubernetes (AWS EKS) and cloud platforms (AWS/Azure).
• Knowledge graphs, vector stores, and embedding techniques.

Responsibilities

• Design and ship production agents on NEO, from prototype through production.
• Build robust retrieval systems using Graph RAG, knowledge graphs, and vector search.
• Design agent memory and secure context management for grounded reasoning.
• Collaborate with product, business, data science, and engineering teams.
• Develop batch and online inference pipelines for ML models.

Skills

Python programming

Kubernetes

AWS / Azure experience

LLM development

MLOps

Information retrieval

Graph RAG

Security/compliance

Data mining

Statistical modeling

Education

MS in Computer Science/Statistics/Mathematics/Machine Learning or related field

Tools

Databricks

SageMaker

MLFlow

OpenSearch/Redis

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
  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
  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.