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AI Product Manager
ICT
💰 Salary Not shared
📊 Market AED 25,000–AED 45,000/mo (AED 300,000–AED 540,000/yr)
About the Company
Open Innovation AI is a global technology company that specializes in developing advanced solutions for managing AI workloads. Its flagship product, the Open Innovation Cluster Manager (OICM), orchestrates complex AI tasks efficiently across diverse infrastructures. The platform is hardware-agnostic, optimized for various GPUs and accelerators hardware, and facilitates seamless integration and scalability for enterprise AI applications. Open Innovation AI focuses on optimizing and simplifying AI workload management and making AI technologies accessible to organizations of all sizes. With its innovative solutions, companies can reduce operational costs, accelerate time to value, and maximize their return on investment, ensuring that their AI strategies contribute directly to enhanced business outcomes.
About the Role
We are looking for 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 to transform foundation models, LLMs, and ML capabilities into reliable, secure, and commercially viable applications. This role requires strong product judgment, technical fluency with modern AI stacks (LLMs, RAG, agents, evaluation frameworks), and the ability to translate ambiguous AI possibilities into measurable business outcomes.
Responsibilities
- ● roduction deployment, governance, and continuous optimization.
- ● Product Strategy & Vision
- ● Define the product vision, roadmap, and success metrics for AI/ML initiatives
- ● Identify high-impact use cases where AI provides defensible value (automation, augmentation, insights)
- ● Translate business problems into AI capabilities and system designs
- ● Balance feasibility, cost (GPU/infra), performance, and ROI
- ● Discovery & Problem Framing
- ● Conduct user research to understand workflows, friction points, and opportunities for intelligence
- ● Validate ideas through rapid experimentation, pilots, and proofs-of-concept
- ● Frame problems as measurable hypotheses (latency, accuracy, cost per request, adoption, etc.)
- ● AI System Design & Delivery (Work closely with engineering to define)
- ● RAG architectures
- ● Agentic workflows
- ● Model selection & benchmarking
- ● Prompt strategies
- ● Evaluation and guardrails
- ● Write clear PRDs and technical specs for AI features
- ● Prioritize features based on impact, risk, and technical complexity
- ● Lead sprint planning and cross-functional execution
- ● Evaluation & Quality
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