Applied AI ML Director

JPMorgan Chase JPMorgan Chase · Banking · Seattle, WA +1 · Corporate Sector

Director level role leading a team of senior AI engineers to build and deploy production-grade agentic AI systems in a regulated financial services environment. Responsibilities include defining architectures, setting standards, ensuring operational excellence, and mentoring the team.

What you'd actually do

  1. Define and evolve agentic AI architectures, including orchestration, retrieval, memory, guardrails, and evaluation
  2. Act as technical authority for applied AI/ML, making architecture decisions and setting production-readiness standards
  3. Stay hands-on by reviewing code, prototyping complex components, and unblocking critical technical challenges
  4. Ensure AI/ML systems are scalable, reliable, secure, observable, and cost-efficient
  5. Oversee delivery of multi-agent systems that automate and scale end-to-end workflows

Skills

Required

  • 10 years of experience building and deploying applied AI/ML systems
  • 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

Nice to have

  • 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
  • Familiarity with financial services or asset and wealth management workflows
  • Track record of hiring and developing senior technical talent
  • Experience fostering a culture of experimentation and innovation

What the JD emphasized

  • production-grade agentic AI systems
  • agentic AI architectures
  • multi-agent systems
  • delivering AI/ML solutions to production at scale
  • regulated environment

Other signals

  • leading a team of senior AI engineers
  • deliver production-grade agentic AI systems
  • define technical direction
  • set engineering standards
  • ensure operational excellence
  • build the next generation of AI systems
  • 10 years of experience building and deploying applied AI/ML systems
  • proven track record delivering AI/ML solutions to production at scale
  • experience collaborating with cross-functional teams in a regulated environment