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AI Product Manager

Open Innovation AI · Abu Dhabi

New
Mid 🇬🇧 English
PRD writing Prompt engineering Roadmap ownership APIs and system architecture LLMs and foundation models Model evaluation benchmarking Cost optimization (tokens/GPU/infra) RAG pipelines Agents and orchestration frameworks Experiment design (A/B testing, offline evals)

Job description

About the role

Open Innovation AI is seeking an AI Product Manager to lead the strategy, design and delivery of AI‑powered products and agentic systems that solve real customer problems at scale. You will work at the intersection of product, engineering, data and business, turning foundation models, LLMs and ML capabilities into reliable, secure and commercially viable applications.

Key responsibilities

  • Define product vision, roadmap and success metrics for AI/ML initiatives, identifying high‑impact use cases and balancing feasibility, cost and ROI.
  • Conduct user research, frame problems as measurable hypotheses and validate ideas through rapid experiments, pilots and proofs‑of‑concept.
  • Collaborate with engineering to design RAG architectures, agentic workflows, select and benchmark models, and write clear PRDs and technical specifications.
  • Establish AI‑specific evaluation metrics (accuracy, hallucination rate, latency, cost per token) and implement evaluation pipelines, red‑team processes and continuous improvement loops.
  • Ensure responsible AI practices by working with security and legal teams on data privacy, bias mitigation, model governance and compliance.

Required profile

  • 4–7+ years of product management or technical product experience delivering complex software or platform products.
  • Strong product judgment with the ability to prioritize, make data‑driven decisions and thrive in ambiguous, fast‑moving environments.
  • Excellent written and verbal communication skills, capable of articulating technical trade‑offs to non‑technical stakeholders.

Required skills

  • PRD writing and roadmap ownership.
  • Prompt engineering and model evaluation benchmarking.
  • LLMs and foundation models, RAG pipelines, agents and orchestration frameworks.
  • APIs and system architecture design.
  • Cost optimization for tokens, GPU and infrastructure.
  • Experiment design (A/B testing, offline evaluations).

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Published 8 hours ago

Expires 1 month from now

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Open Innovation AI

Abu Dhabi