AI Agents Applied Research/Engineering Lead - Vice President

JPMorgan Chase & Co. • New York, NY

1d

About The Position

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.

Chase serves over 80 million customers and is building the next generation of
conversational AI to power personalized financial decision-making across travel,
banking, lifestyle services, and more. We're looking for an AI Agents Applied
Research/Engineering Lead to drive the research, design, and deployment of
agentic AI systems at the heart of that effort.

As AI Agents Applied Research/Engineering Lead, 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.

You'll have the opportunity to publish at top-tier venues like NeurIPS, ICML,
and ACL—and see that research deployed to a user base of over 80 million
customers.

Requirements

• Ph.D. with 1+ years or M.S. with 3+ years building and deploying AI systems in production
• Applied GenAI experience with LLMs including fine-tuning, prompt engineering, and RAG.
• Experience scaling LLM systems with caching, batching, governance, and evaluation.
• Strong foundation in ML, deep learning, statistical modeling, and experimental design.
• Experience in Information Retrieval (indexing, ranking, retrieval) and/or recommendation systems.
• Proficiency in Python and ML frameworks (PyTorch/TensorFlow, Hugging Face, scikit-learn)
• Demonstrated ability to set a technical research agenda and drive it from concept through production deployment.
• Experience presenting research findings and technical strategy to senior leadership and non-technical stakeholders.

Nice To Haves

• 5+ years developing conversational AI systems, virtual assistants or LLM-based systems in production.
• Experience with multi-agent orchestration, supervisor agents, and specialized toolkits.
• Expertise in agent governance, red-teaming, adversarial testing, and safety evaluation.
• Experience with reinforcement learning, bandit algorithms, and preference-based optimization (DPO, IPO), with practical exposure to data collection, labeling, and evaluation pipelines.
• MLOps/LLMOps experience with CI/CD, monitoring, versioning, A/B testing, and rollbacks.
• Track record of data-driven product development and experimentation.
• Publications in top-tier AI/ML venues and/or open-source contributions

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.

Benefits

• We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees