Lead Machine Learning Engineer - Agentic Pricing
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 22d ago
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Job Location
Jersey City, NJ, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
JPMorganChase is seeking top talent to join their Corporate & Investment Bank Technology organization, focusing on building production AI agents on the NEO platform. This role involves designing, productionizing, and operating large language model (LLM)-powered agents in a fast-paced environment, partnering closely with business, product, and engineering teams. You will contribute to a federated portfolio of production agents that deliver measurable impact across the Commercial & Investment Bank and Payments, leveraging the firm's scale, data, and full-service advantage.
Responsibilities
- Design and ship production agents on NEO, owning them from prototype to production.
- Build production-ready retrieval systems with effective chunking, ranking, and grounding strategies.
- Design agent memory systems, including episodic and semantic memory with recall, summarization, and decay policies.
- Manage organizational context, ensuring agents reason over appropriate data based on entitlement, lineage, and tenant.
- Compose multi-agent workflows using A2A and integrate tools and data via MCP servers.
- Build and run evaluations for agents, including task-level, end-to-end, regression suites, and LLM-as-judge.
- Deploy and operate solutions on public cloud (AWS/Azure) with strong SDLC, security, resiliency, and observability practices.
- Partner with product and business stakeholders to translate use cases into shipped agents.
Requirements
- MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).
- Minimum 7 years of development experience, with at least 4 years in AI/ML solutions.
- Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.
- Strong Python programming skills 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, Kubernetes.
- Knowledge of data management and data model design, including real-time processing with SQL and NoSQL stores.
- Excellent communication skills for effective stakeholder partnerships.