About The Position

We’re hiring an AI Deployment Manager to help customers implement, scale, and succeed with Motion’s AI Employees. This role sits at the intersection of customer operations, product, and engineering. You’ll be the one who ensures our agents deliver measurable outcomes for customers — not just pilots or demos, but real, ongoing deployments that transform how they work. It’s technical: you’ll be inside prompts, configs, APIs, and data pipelines. It’s operational: you’ll own deployments end-to-end, from scoping to adoption. It’s customer-facing: you’ll work directly with executives and ICs to understand their workflows and design solutions. This is not an easy role. It’s intense, iterative, and requires persistence. You won’t work 9–5 — you’ll grind, you’ll push, and if you’re wired for this kind of work, you’ll grow faster than anywhere else.

Requirements

  • 3–5 years in solutions engineering, implementation, consulting, or forward-deployed roles (SaaS/startup preferred).
  • Comfort working directly with customers to analyze workflows and deploy technology.
  • Technical aptitude: you don’t need to be a software engineer, but you can read configs, experiment with prompts, and handle APIs without fear.
  • Strong project management skills: you can take fuzzy problems, structure them into plans, and get them over the line.
  • Ownership mindset: you run deployments end-to-end, no excuses.
  • Excellent communication: equally comfortable in the weeds with ICs and presenting to execs.
  • Excitement for AI: you stay curious, experiment with tools, and understand where the tech shines vs. where it fails.
  • High pain tolerance: this is not an easy job. It’s intense, messy, and high stakes — but if you can push through, the payoff is huge.

Responsibilities

  • Lead AI Employee deployments from kickoff through scale, ensuring customers see measurable business impact.
  • Map customer workflows, identify automation opportunities, and design deployment plans.
  • Configure and customize Motion’s AI Employees: prompts, workflows, API connections, and internal tools.
  • Partner with engineering and product to close gaps uncovered in the field; push for features that unlock more automation.
  • Act as the technical guide for customers — showing them how to use agents effectively and where the technology is strong vs. weak.
  • Build repeatable playbooks and best practices for deploying AI in different verticals.
  • Own adoption metrics: usage, coverage, and value delivered.
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