Deployment Program and Operation Manager

Posted 3 Days Ago
7 Locations
In-Office or Remote
Entry level
Artificial Intelligence • Machine Learning • Robotics
The Role
Lead customer robot deployments from workflow discovery and site assessment through scoping, financial modeling, technical alignment, execution, acceptance testing, training, and handoff. Partner with engineering, research, safety, solution engineering, customers, and external teams to define requirements, success metrics, dependencies, and milestones. Translate field feedback into deployment practices while managing scope changes, implementation tradeoffs, customer value, utilization, and support needs.
Summary Generated by Built In
About Genesis

We are a full-stack general-purpose robot company, born across San Francisco and Paris and bound by a single mission: to make general-purpose robots a reality, unlocking infinite physical labor for the world and freeing people for creativity, exploration, and the pursuits they love for their own sake.

We are French and American by birth and global by nature. We are backed by partners who share our vision, including Eclipse, Khosla Ventures, Bpifrance, and HSG, alongside Eric Schmidt, Xavier Niel, Daniela Rus, and Vladlen Koltun. Our people work across the Bay Area and Europe, building the engine that will teach robots to do real work in the real world. We recently unveiled Eno, our wheeled, dexterous robot powered by our GENE foundation model, and we are starting to put it to work with real customers.

What You'll Do
  • Turn customer workflows into clearly scoped deployments, using site visits and operator interviews to define requirements, success metrics, and acceptance criteria.

  • Build deployment financial models and assess customer value, utilization, implementation costs, and support needs to inform scope and rollout decisions.

  • Partner with Deployment Solution Engineers, research, engineering, and safety specialists to align technical capabilities with customer requirements and site readiness.

  • Drive cross-functional execution from scoping through customer acceptance, keeping milestones, dependencies, scope changes, and decisions clear across distributed teams.

  • Coordinate acceptance testing, training, and handover, and turn field feedback and competitive insights into reusable deployment practices.

What You'll Bring
  • A track record of taking complex technical initiatives from ambiguous customer needs through launch and adoption.

  • Strong analytical judgment, with experience building financial models and evaluating costs, resource constraints, and implementation tradeoffs.

  • Enough technical fluency to work with robotics, software, and AI teams, question assumptions, and translate field issues into clear requirements.

  • A strong bias toward the field, with the ability to learn directly from operators and communicate requirements, decisions, and tradeoffs clearly in writing.

  • Comfort driving alignment and execution with incomplete information across customers, engineers, and external partners.

  • Bonus: Experience in robotics, autonomy, industrial technology, or enterprise systems where success depends on reliable real-world performance.

Skills Required

  • Track record of taking complex technical initiatives from ambiguous customer needs through launch and adoption
  • Experience building financial models and evaluating costs, resource constraints, and implementation tradeoffs
  • Technical fluency sufficient to work with robotics, software, and AI teams and translate field issues into requirements
  • Ability to learn directly from operators and communicate requirements, decisions, and tradeoffs clearly in writing
  • Ability to drive alignment and execution with incomplete information across customers, engineers, and external partners
  • Experience in robotics, autonomy, industrial technology, or enterprise systems
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The Company
86 Employees
Year Founded: 2025

What We Do

Genesis AI is a global full-stack robotics company developing general-purpose robots with human-level intelligence and capabilities. It aims to build foundational AI models that automate repetitive tasks across applications such as lab work and housekeeping. The company uses a proprietary physics engine to generate synthetic physical-world data, helping train robotics models for diverse real-world environments, and operates across Paris and Silicon Valley.

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