AI Agents Applied Research Engineering Lead Vice President
JPMorganChase
Job Overview
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Job Description
About the Role
As an AI Agents Applied Research/Engineering Lead in our The Digital Team, you will work with the team to shape how millions of customers discover, decide, and act—turning multi-step financial tasks into simple conversations. You'll lead the end-to-end lifecycle of LLM-based agents: defining research directions in areas like multi-step planning, tool use, and safety; building production systems that perform under real-world latency, accuracy, and compliance constraints; and partnering with Product, Engineering, Design, and Risk teams to bring those systems to market. The problems here are genuinely unusual—building AI that must be not just accurate but auditable, explainable, and safe in a highly regulated, high-stakes domain. Transform how millions of customers manage their money, make decisions, and get more from their financial relationships through a human-centered approach that blends cutting-edge AI with clear, trustworthy experiences.
Job Responsibilities
- Lead research and deployment of agentic AI systems with multi-step workflows, tool calling, and multi-agent orchestration.
- Fine-tune and optimize LLMs using parameter-efficient fine-tuning (PEFT), distillation, and quantization to meet production constraints such as latency, memory, and cost.
- Apply reinforcement learning and preference optimization to improve personalization and dialogue policies.
- Scale LLM systems through caching, batching, prompt governance, and evaluation frameworks.
- Implement privacy, safety, and security controls including PCI compliance, jailbreak resistance, and auditability.
- Design rigorous experiments with strong baselines and meaningful metrics.
- Define and track success metrics for agent performance, including task completion rate, accuracy, latency, and customer satisfaction.
Key skills/competency
- AI Agents
- Applied Research
- Engineering Lead
- LLM
- Multi-step Planning
- Tool Use
- Safety
- Production Systems
- Reinforcement Learning
- MLOps
How to Get Hired at JPMorganChase
- Tailor your resume: Highlight your Ph.D./M.S. with relevant years of experience in building and deploying AI systems, specifically applied GenAI with LLMs, fine-tuning, prompt engineering, RAG, and scaling LLM systems.
- Showcase your expertise: Emphasize your proficiency in Python and ML frameworks (PyTorch/TensorFlow, Hugging Face, scikit-learn), and experience with Information Retrieval or recommendation systems.
- Demonstrate leadership: Provide examples of setting a technical research agenda and driving it from concept to production, and experience presenting to senior leadership.
- Highlight preferred qualifications: If applicable, mention experience with conversational AI, multi-agent orchestration, agent governance, RL, and MLOps/LLMOps.
- Prepare for technical and behavioral interviews: Be ready to discuss your research, deployment experience, and how you handle complex, regulated AI challenges.
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