Lead Machine Learning Engineer - Generative AI and Agent Platforms

JPMorgan Chase offers a competitive total rewards package designed to support your growth and well being. This onsite Jersey City opportunity centers on building and operating production grade AI agents and agent platforms for payments technology, applying enterprise scale MLOps across the platform and business units.

Benefits

• Base salary
• Health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching
• Commission-based pay and/or discretionary incentive compensation (cash and/or forfeitable equity)

Responsibilities

• Design and deliver production ready AI agents across a federated portfolio, guiding solutions from prototype through launch and ongoing operations
• Engineer reliable retrieval systems for production use, including hybrid retrieval-augmented generation patterns with vector search and graph-based retrieval where appropriate, plus robust chunking, ranking, and grounding
• Implement memory patterns for agents, covering episodic and semantic memory with recall, summarization, and decay policies aligned to use-case needs
• Assemble entitlement-aware and tenant-aware context so agents reason only over permitted data, enabling traceability and auditability
• Orchestrate multi-agent workflows and integrate external tools and data sources through secure connectors and standardized interfaces
• Develop evaluation frameworks spanning task-level and end-to-end assessments, regression suites, automated scoring, and release gates for quality and safety
• Deploy and operate agent services on public cloud platforms such as AWS and/or Azure, applying rigorous software development lifecycle, security, resiliency, and observability practices
• Improve runtime performance and reliability by instrumenting tracing, monitoring, and incident-response playbooks for agent services
• Collaborate with product and business leaders to translate use cases into shipped capabilities, define success metrics, and drive improvements from production feedback

Requirements

• Formal training or certification in applied AI and machine learning concepts with 5+ years of 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 AI or ML 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 with solid fundamentals in data structures, algorithms, and applied statistics
• Practical experience with retrieval-augmented generation, embedding strategies, retrieval quality measurement, and vector databases
• Proficiency operating production workloads in AWS, Azure, or Kubernetes
• Experience designing data models and building systems using SQL and NoSQL technologies for real-time or near real-time use cases
• Strong communication skills and ability to partner effectively with senior technical and business stakeholders

Technologies

• Databricks
• GenAI Gateway
• Amazon Web Services
• Microsoft Azure
• Kubernetes
• Python
• Vector databases
• Go
• Rust
• JavaScript
• TypeScript
• Graph databases
• SQL
• NoSQL