AI Agents Applied Research Engineering Lead - Executive Director

JPMorganChase; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

comprehensive health care coverage

on-site health centers

retirement savings plan

backup childcare

tuition reimbursement

mental health support

financial coaching

Job summary

JPMorgan Chase & Co. in Bengaluru seeks an AI Agents Applied Research/Engineering Executive Director to shape how millions of customers discover, decide, and act.

You will lead end-to-end lifecycle of LLM-based agents, collaborating with Product, Engineering, Design, and Risk to bring auditable, safe systems to market. You will drive research directions in multi-step planning, tool use, and safety, while building production systems meeting latency and regulatory constraints for a high-stakes

Qualifications

• 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 and/or recommendation systems.
• Proficiency in Python and ML frameworks (PyTorch/TensorFlow, Hugging Face, scikit-learn).
• 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.

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, distillation, and quantization to meet production constraints.
• 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.

Skills

GenAI experience

LLMs fine-tuning

Python

ML frameworks

research agenda

Education

Ph.D. with 8+ years

M.S. with 12+ years

Tools

PyTorch

TensorFlow

Hugging Face

Job description

Job Description

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. Youll 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. Youll 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

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.

• comprehensive health care coverage
• on-site health and wellness centers
• retirement savings plan
• backup childcare
• tuition reimbursement
• mental health support
• financial coaching

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.