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Enterprise AI Deployment

AI Delivery Lead / Technical Program Manager

Create the delivery rhythm, visibility and accountability that moves AI initiatives from experimentation into controlled production.

Remote, Time-Zone Requirements ApplyFull-time or project basedReferral reward $250
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About this path

This role coordinates product, engineering, data, security, legal, operations and client leadership. It explicitly manages evaluation, data, adoption and production-readiness risks without turning delivery into unnecessary administration.

You will create the delivery rhythm that keeps an AI initiative moving from experimentation toward controlled production, coordinating product, engineering, data, security, legal and client leadership. The job is managing real risk around evaluation, data and adoption without burying the team in unnecessary process. It fits program managers who protect momentum as much as they protect quality.

What you would own

  • Delivery planning and cadence across cross-functional AI initiatives
  • Coordination between product, engineering, data, security, legal and client teams
  • Risk management around evaluation, data quality and adoption readiness
  • Status reporting and visibility for client and internal leadership
  • Escalation and resolution of blockers before they derail timelines
  • Balance between necessary process and unnecessary administrative overhead

You are likely a strong match if

  • You have technical program management or delivery leadership experience
  • You can coordinate across product, engineering, data, security and legal teams
  • You manage real project risk, not just status updates
  • You know when to add process and when to remove it
  • You communicate clearly with both technical teams and client leadership
  • You have some understanding of AI-specific delivery risks such as evaluation and data quality

Helpful, not required

  • Formal program management certification
  • Experience running enterprise software delivery programs
  • Familiarity with AI evaluation and governance practices
  • Experience managing client-facing delivery relationships

What success looks like

  • AI initiatives move from experimentation to production on a credible timeline
  • Risks around evaluation, data and adoption are surfaced early
  • Client and internal leadership have accurate, timely visibility into status
  • Delivery process stays lean enough not to slow the team down

Practical proof that helps

  • A case study of a cross-functional AI or technical program you delivered
  • Examples of status reporting or risk-tracking artifacts you have used
  • References from stakeholders on a program you led

What being in the network gives you

  • Remote-first work with clients across the United States, Canada and Latin America.
  • Human review of your profile, automation organizes information, people decide.
  • One profile considered across current and future opportunities.
  • Referral rewards when someone you refer directly is successfully placed.
  • Full control over availability, matching and your data at any time.

One profile, many opportunities

Applying here creates a single reusable profile. If this path is not the right fit, you remain eligible for other suitable opportunities across the network.

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