Lead Machine Learning Engineer - Agentic AI

Jpmorganchase — United Kingdom · Posted ~18 hours ago

Lead Full-time Visa History ✓

Skills

Machine learning LLM Agentic AI MLOps Productionization Continuous delivery AI engineering

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

Shape production-grade AI solutions as a Lead Machine Learning Engineer. You will design, productionize, and operate LLM-powered agents for business workflows, apply MLOps for automation and continuous delivery, and collaborate with business, product, data science, and engineering teams to expand a portfolio of reliable AI agents in a secure, regulated environment.

Highlights

Lead AI/ML role focused on production-grade LLM agents, MLOps automation, continuous delivery, and collaboration across business, product, data science, and engineering teams in a regulated environment.

Description

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 productionBuild robust retrieval systems using Graph RAG, knowledge-graph traversal, vector search, chunking, ranking, and grounding strategiesDesign agent memory, including episodic and semantic memory nodes, recall, summarization, and decay policiesManage organizational context, assembling entitlement-, lineage-, and tenant-aware context for secure agent reasoningCompose 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 gatingDeploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC, security, resiliency, and observability practicesPartner with product and business teams to turn use cases into shipped, supported agentsBuild traditional ML model training pipelines and productionize them using MLOps best practicesDevelop 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 guardrailsStrong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statisticsKnowledge of Kubernetes (AWS EKS)Experience with training models in Databricks and SageMakerExperience working with MLFlowPractical RAG experience—retrieval quality, embeddings, and vector stores; Graph RAG a strong plusExpert knowledge of at least one of: AWS, Azure, KubernetesKnowledge 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 MCPAgent memory design (memory nodes, episodic/semantic memory) and organizational context managementKnowledge graphs and graph databases used for retrievalUnderstanding of LLM fine-tuning and small language model inferenceAbility 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 US 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. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team 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.