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Artificial Intelligence Portfolio and Platform Lead

datadotorg

datadotorg

Software Engineering
Seattle, WA, USA · Remote
USD 233,600-362,200 / year
Posted on Apr 8, 2025

In A Nutshell

Location

Hybrid Seattle, WA, USA

Salary

$233,600-$362,200

Job Type

Full-time

Experience Level

Mid-level

Visa Sponsorship

Not Available

Deadline to apply

April 29, 2025

Play a central role in managing the lifecycle of AI projects, from proof-of-concept to regional or national scale.

Responsibilities

Portfolio and Product Management

  • Manage the full lifecycle of AI projects, ensuring seamless transitions from concept to scale.
  • Develop and implement portfolio management frameworks to track project timelines, budgets, and milestones.
  • Support the assessment of project’s readiness to advance to future development phases.
  • Identify and address product bottlenecks.
  • Ensure full portfolio of products are positioned to address full scope of AI strategy.

Stakeholder Coordination and Strategy

  • Collaborate with AI teams, technical experts, grant managers, and external partners to align product strategies with organizational goals.
  • Build strong relationships with governments, funders, and implementation partners to facilitate AI adoption.
  • Develop clear strategies for AI product introduction, ensuring solutions are viable in LMIC contexts.

Scaling and Resource Optimization

  • Identify high-potential AI initiatives and guide them through the maturity pipeline.
  • Identify barriers to scale and ensure products are linked with relevant technical and non-technical enablers and other AI workstreams.
  • Recommend resource allocation strategies to maximize impact and efficiency.
  • Streamline investment decisions by providing data-driven insights on AI project performance.

Deliverables

  • AI Project Roadmap, Timelines & Dashboards – Centralized tracking system for prioritized AI initiatives.
  • Annual Portfolio Performance Report – Summary of progress, challenges, and strategic recommendations.
  • Scaling Readiness Framework – Standardized approach for evaluating AI projects, ensuring key enablers (such as regulatory pathway, compute and data access, and benchmarks for evaluation) are achieved before each stage gate of the team’s maturity model.
  • Stakeholder Engagement Plan – Strategy for ensuring buy-in from key partners in LMICs.

Skillset

  • Advanced degree biotech/pharmaceutical/ life sciences or equivalent.
  • 8+ years of experience managing AI, digital, or technology product portfolios, ideally in a commercial setting.
  • Strong understanding of AI product development, evaluation, and adoption.
  • Experience in structuring and managing AI projects, tracking deliverables, and managing cross-functional teams.
  • Ability to engage with governments, donors, and implementing partners to drive AI adoption; familiarity in engaging with tech firms.
  • Strong analytical skills to assess project performance and resource allocation.
  • Familiarity with the challenges of scaling AI solutions in LMIC contexts preferred.

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