Join JPMorgan Chase and help shape the future of AI-driven innovation in financial services.
As an Applied AI / ML Director in AI ML & Data Platform Team, you will lead, mentor, and inspire a team of senior AI engineers to deliver production-grade agentic AI systems. You will partner with us to define technical direction, set engineering standards, and ensure operational excellence across multiple use cases. Your leadership will drive innovation, foster a culture of experimentation and responsible AI, and help us deliver solutions that make a measurable business impact. Together, we will build the next generation of AI systems for the firm.
Job Responsibilities:
- Define and evolve agentic AI architectures, including orchestration, retrieval, memory, guardrails, and evaluation
- Act as technical authority for applied AI/ML, making architecture decisions and setting production-readiness standards
- Stay hands-on by reviewing code, prototyping complex components, and unblocking critical technical challenges
- Ensure AI/ML systems are scalable, reliable, secure, observable, and cost-efficient
- Partner with platform, data, and infrastructure teams on distributed systems and training/serving patterns
- Lead, mentor, and grow a high-performing team of applied AI/ML engineers
- Set clear technical expectations, career paths, and standards of excellence
- Foster a culture of strong engineering fundamentals, experimentation, and responsible AI practices
- Hire senior technical talent and raise the bar across the organization
- Oversee delivery of multi-agent systems that automate and scale end-to-end workflows
- Collaborate with product, risk, legal, and compliance partners to ensure solutions are innovative and deployable
Required Qualifications, Capabilities, and Skills:
- 10 years of experience building and deploying applied AI/ML systems, with significant recent hands-on work
- Experience leading and managing teams of senior engineers
- Deep understanding of machine learning and AI fundamentals, including modern generative AI and LLM-based systems
- Proven track record delivering AI/ML solutions to production at scale
- Strong familiarity with distributed systems for training, inference, and state management
- Ability to communicate complex technical trade-offs to both technical and non-technical stakeholders
- Demonstrated experience setting engineering standards and driving operational excellence
- Experience collaborating with cross-functional teams in a regulated environment
- Strong coding and code review skills in Python and modern ML frameworks
- Commitment to responsible AI practices and continuous improvement
- Ability to mentor and develop engineering talent
Preferred Qualifications, Capabilities, and Skills:
- Experience with agentic systems, multi-agent architectures, and LLM evaluation frameworks
- Experience deploying AI workloads on AWS (e.g., SageMaker, Bedrock) or equivalent platforms
- Background building AI systems in regulated or high-reliability environments
- Experience integrating user feedback loops for continuous model and system improvement
•