Senior AI Agent Engineer — Production LLMs for Pricing

Aumni; Jersey City (NJ); Sur place; USD 150 000 - 230 000; Plein temps

Avantages offerts par ce poste

Health insurance

On-site health centers

Retirement savings plan

Tuition reimbursement

Mental health support

Résumé du poste

JPMorgan Chase & Co. is seeking a Senior AI Application Engineer to design, productionize, and operate LLM-powered agents on the NEO runtime platform, across the Corporate & Investment Bank and Payments divisions.

You will deploy on AWS/Azure, ensure MLOps governance, and collaborate with business and product teams to ship impactful AI solutions. The role emphasizes building production-grade AI systems with robust retrieval, memory design, and multi-agent workflows, while complying with

Qualifications

• 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 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 — retrieval quality, embeddings, and vector stores.
• Expert knowledge of at least one of: AWS, Azure, Kubernetes.
• Knowledge of data management and data model design; real-time processing using both 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.

Responsabilités

• Design and ship production agents on NEO across the federated portfolio, owning them from prototype through production.
• Build retrieval that holds up in production: chunking, ranking, and grounding strategies that keep answers accurate and auditable.
• Design agent memory: episodic and semantic memory organized as memory nodes, with recall, summarization, and decay policies tuned per use case.
• Own organizational context management — assembling entitlement-, lineage-, and tenant-aware context so each agent reasons over only what it’s allowed to see.
• Compose multi-agent workflows using A2A, and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk).
• Build and run evals: task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, and quality/safety gating before release.
• Deploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC, security, resiliency, and observability practices.
• Partner with product and business partners across the Corporate & Investment Bank and Payments to turn use cases into shipped, supported agents.

Connaissances

Python

LLM Apps

RAG

AWS

Azure

Kubernetes

Data modeling

Communication

Formation

MS in Computer Science or related field

Outils

Databricks

Bitbucket

Confluence

Snowflake

Splunk

Description du poste

JPMorgan Chase & Co. is seeking a Senior AI Application Engineer to design, productionize, and operate LLM-powered agents on the NEO runtime platform, across the Corporate & Investment Bank and Payments divisions.

You will deploy on AWS/Azure, ensure MLOps governance, and collaborate with business and product teams to ship impactful AI solutions. The role emphasizes building production-grade AI systems with robust retrieval, memory design, and multi-agent workflows, while complying with