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AI Deployment Engineer (San Francisco)

Formant

Salary not specified
Sep 25, 2025
San Francisco, CA, US
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Formant is building the operating system for intelligent machines to unlock the full potential of robotics by making it effortless to manage, operate, and scale heterogeneous fleets—powered by AI. The AI Deployment Engineer will bridge the gap between cutting-edge AI capabilities and real-world robotics/physical deployments, transforming customer operations by integrating AI into their physical environment.

Requirements

  • Deep experience with production AI/ML systems, including LLMs, computer vision, and sensor fusion

Responsibilities

  • Design and build LLM powered workflows, RAG pipelines and custom AI solutions tailored to specific robotic/physical use cases
  • Create reusable frameworks and tools that accelerate future deployments across our customer base
  • Serve as the AI expert in customer engagements, translating between technical requirements and business value
  • Collaborate with product to incorporate field insights and customer feedback into our platform roadmap and AI capabilities
  • Enable customer teams through training, documentation, and knowledge transfer for sustainable AI Adoption
  • Lead AI Implementations for enterprise robotics/physical customers, from initial discovery through production deployment
  • Embed with customers on-site to understand their operations, identify AI opportunities, and implement solutions that drive measurable ROI

Other

  • Located in the San Francisco area to occasionally go to the office to interact with our robots.
  • Track record of driving customer success through technical solutions in complex enterprise environments
  • Genuine passion for the intersection of AI and physical world and applications
  • Thrive in ambiguous situations, turning vague requirements into concrete technical solutions
  • Ability to explain complex architectures to executives and discuss business strategy with engineers
  • Quickly master new domains, from warehouse operations to agricultural workflows
  • Bias towards rapid prototyping and iteration over perfect theoretical solutions