Senior Generative AI & Agent Platform Engineer

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. within Payments Technology, Data Analytics, Regulatory & Compliance (Data Analytics) in the Commercial & Investment Bank seeks an Applied AI and Machine Learning Lead to build and operate a platform for agentic AI.

You will own end‑to‑end AI solutions, combining engineering discipline with safety, evaluation, and enterprise‑scale reliability. You will partner with product, engineering, and business stakeholders to deliver auditable AI capabilities, applying memory,

Qualifications

• Formal training or certification on applied AI and machine learning concepts and 5+ years applied experience
• Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience
• Minimum 7 years of software development experience, including at least 4 years delivering artificial intelligence or machine learning solutions
• Hands‑on experience building large language model‑powered or agentic applications in production, including tracing, evaluations, and safety guardrails
• Strong programming skills in Python, including strong fundamentals in data structures, algorithms, and applied statistics
• Practical experience with retrieval‑augmented generation, including embedding strategies, retrieval quality measurement, and use of vector databases
• Proficiency operating production workloads in at least one of the following: Amazon Web Services, Microsoft Azure, or Kubernetes
• Experience designing data models and building systems using both SQL and NoSQL technologies for real‑time or near‑real‑time use cases
• Strong communication skills and the ability to partner effectively with senior technical and business stakeholders

Responsibilities

• Design and deliver production AI agents across a federated portfolio, owning solutions from prototype through launch and operational support
• Engineer retrieval systems that perform reliably in production, including hybrid retrieval‑augmented generation patterns with robust chunking, ranking, and grounding approaches
• Implement agent memory patterns, including episodic and semantic memory with recall, summarization, and decay policies aligned to use‑case needs
• Build entitlement‑aware and tenant‑aware context assembly so agents reason only over permitted data, supporting traceability and auditability
• Orchestrate multi‑agent workflows and integrate external tools and data sources through secure connectors and standardized tool interfaces
• Develop evaluation frameworks, including task‑level and end‑to‑end evaluations, regression suites, automated scoring, and release gates for quality and safety
• Deploy and operate agent services on public cloud platforms (AWS and/or Azure), applying strong SDLC, security, resiliency, and observability practices
• Optimize runtime performance and reliability by instrumenting tracing, monitoring, and incident‑response playbooks for agent services
• Partner with product and business leaders to translate use cases into shipped capabilities, define success metrics, and drive continuous improvement based on production feedback

Skills

Python

Algorithms

Applied statistics

AI/ML concepts

Strong communication

Education

Bachelor's degree in CS/Engineering/Math/Statistics

Tools

Databricks

Kubernetes

Vector databases

Go

Rust

JavaScript/TypeScript

Job description

JPMorgan Chase & Co. within Payments Technology, Data Analytics, Regulatory & Compliance (Data Analytics) in the Commercial & Investment Bank seeks an Applied AI and Machine Learning Lead to build and operate a platform for agentic AI.

You will own end‑to‑end AI solutions, combining engineering discipline with safety, evaluation, and enterprise‑scale reliability. You will partner with product, engineering, and business stakeholders to deliver auditable AI capabilities, applying memory,