We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. 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.
As an AI Agents Applied Research/Engineering Executive Director 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.
Required Qualifications, Capabilities, and Skills
- Ph.D. with 8+ years or M.S. with 12+ 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.
Preferred Qualifications, Capabilities, and Skills
- 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
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Skills Required
- Ph.D. with 8+ years or M.S. with 12+ 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
- 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)
- 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
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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