Robotics Deployment & Operations Lead

Genesis AI; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

Genesis AI is seeking a Deployment-focused professional to translate customer workflows into clearly scoped robotic deployments. You will collaborate with operations, engineering, and safety teams to align technical capabilities with site readiness and drive end-to-end deployment execution.

The role emphasizes analytical modeling, field-based requirements gathering, and a strong bias toward practical, real-world performance of autonomous systems.

Qualifications

• Track record taking complex technical initiatives from ambiguous needs through launch and adoption.
• Strong ability to build and evaluate financial models and cost/resource tradeoffs.
• Fluency to work with robotics, software, and AI teams and translate field issues into requirements.
• Ability to learn from operators and communicate decisions clearly in writing.
• Capable of aligning stakeholders across customers, engineers, and external partners.

Responsibilities

• Turn customer workflows into clearly scoped deployments using site visits and interviews.
• Build deployment financial models and assess value, utilization, costs, and support needs.
• Partner with Deployment Solution Engineers, research, engineering, and safety specialists to align capabilities with requirements and site readiness.
• Drive cross-functional execution from scoping to customer acceptance with clear milestones and changes.
• Coordinate acceptance testing, training, and handover, turning field feedback into reusable deployment practices.

Skills

Technical ownership

Analytical judgement

Technical fluency

Written communication

Cross-functional alignment

Robotics/AI domain familiarity

Job description

Genesis AI is seeking a Deployment-focused professional to translate customer workflows into clearly scoped robotic deployments. You will collaborate with operations, engineering, and safety teams to align technical capabilities with site readiness and drive end-to-end deployment execution.

The role emphasizes analytical modeling, field-based requirements gathering, and a strong bias toward practical, real-world performance of autonomous systems.