Applied AI ML Lead - Machine Learning Engineer - Agentic Commerce

JPMorgan Chase & Co.; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead AI and ML Engineer to design, productionize, and operate LLM-powered agentic solutions on NEO. You will implement Graph RAG, create robust retrieval systems, and ensure secure, auditable AI deployments across CIB and Payments.

You will collaborate with business, product, data science, and engineering teams to expand the portfolio of production agents with strong SDLC, security, and observability practices.

Qualifications

• MS or equivalent experience in a relevant field
• Hands-on experience building production ML/LLM solutions
• Strong Python, data structures, algorithms, ML basics
• Kubernetes in production environments
• Experience with Databricks and SageMaker
• Experience with MLFlow and RAG retrieval
• Knowledge of AWS/Azure/Kubernetes
• Data management and real-time processing capabilities

Responsibilities

• Design and ship production agents on NEO from prototype to production
• Build robust retrieval systems using Graph RAG and vector stores
• Design agent memory including episodic and semantic memory
• Manage context and security for agent reasoning
• Compose multi-agent workflows using A2A and MCP integrations
• Develop ML training pipelines and MLOps best practices
• Deploy and operate solutions on AWS/Azure with strong SDLC and observability
• Collaborate with product/business teams to ship supported agents
• Develop batch and online inference for ML models

Skills

Python programming

Kubernetes (AWS EKS)

Databricks

SageMaker

MLFlow

Graph RAG

LLM-powered apps

NLP/AI engineering

.communication

Education

MS in CS/Stats/Math/ML or equivalent

Tools

Databricks

SageMaker

MLFlow

Kubernetes (AWS EKS)

Postgres

OpenSearch/Redis

Job description

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.

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.

Job Responsibilities

• 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

Required Qualifications, Capabilities, and Skills

• 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

Preferred Qualifications, Capabilities, and Skills

• 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