below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$202,800–$254,750.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
Lead Machine Learning Engineer - Agentic Pricing joins the Corporate & Investment Bank Technology organization within Digital & Platform Services / Data Analytics. As a Senior AI Application Engineer, you will design, productionize, and operate large language model-powered agents on the NEO agent runtime platform. Your daily responsibilities include building retrieval strategies, designing episodic and semantic memory, and composing multi-agent workflows using A2A communication. You will integrate tools through MCP servers including Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, and Splunk. Required skills include Python, SQL, NoSQL stores like OpenSearch or Redis, and expertise in AWS, Azure, or Kubernetes. You will solve complex problems in the Commercial & Investment Bank and Payments sectors by developing production-grade agents that handle forecasting, anomaly detection, and sales fulfillment within a regulated environment.
Design and ship production-ready AI agents on the NEO platform from prototype to deployment.
Build production-grade retrieval systems using chunking, ranking, and grounding strategies to ensure accuracy.
Design agent memory systems featuring episodic and semantic memory with custom recall and decay policies.
Manage organizational context to ensure agents reason only over data they are authorized to access.
Compose multi-agent workflows using agent-to-agent communication and integrate tools via MCP servers.
Build and run end-to-end evaluations, regression suites, and safety gating before production release.
Deploy and operate AI solutions on AWS and Azure using robust SDLC, security, and observability practices.
What we're looking for
MS in Computer Science, Statistics, Mathematics, Machine Learning, or a related field or equivalent experience.
Minimum 7 years of development experience.
At least 4 years of experience working on AI/ML solutions.
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.
Practical RAG experience including retrieval quality, embeddings, and vector stores.
Expert knowledge of at least one of AWS, Azure, or Kubernetes.
Knowledge of data management, data model design, and real-time processing using SQL and NoSQL stores.
Excellent communication skills to partner with senior technical and business stakeholders.
Graph RAG experience (preferred).
Experience with agent frameworks or runtimes, A2A, or MCP (preferred).
Agent memory design and organizational context management (preferred).
Knowledge graphs and graph databases used for retrieval (preferred).
Understanding of LLM fine-tuning and small language model inference (preferred).
Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (preferred).
Experience working in the financial or payments domain at a large institution (preferred).
Knowledge of high-performance languages such as Go or Rust (preferred).