Proficient AI COE
OmantelOman13 days ago
Full-timeOther
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Role Purpose
To manage and governing discovery, delivery, and governance of enterprise AI across the organization, ensuring AI initiatives are business-outcome driven, responsibly governed, secure, and successfully adopted at scale. The role spans use‑case portfolio management, solution incubation, MLOps/LLMOps, and value realization through measurable KPIs.
Position Information
Title: Proficient, AI (COE)
To manage and governing discovery, delivery, and governance of enterprise AI across the organization, ensuring AI initiatives are business-outcome driven, responsibly governed, secure, and successfully adopted at scale. The role spans use‑case portfolio management, solution incubation, MLOps/LLMOps, and value realization through measurable KPIs.
Position Information
Title: Proficient, AI (COE)
- Unit: Strategy and Innovation
- Division: Center of Excellence
- Location: Muscat
- Grade:
- Proficient: P5
- Minimum role requirements:
- Qualifications: Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; advanced degree preferred. Certifications in cloud AI/ML (e.g., Azure AI Engineer, AWS Machine Learning, Google Professional ML Engineer) and Responsible AI are a plus.
- Experience:
- Proficient: A minimum of 7 years’ experience
- Drive discovery and prioritization of AI/ML use cases aligned to business value and strategic goals.
- Govern intake, triage, and planning of AI initiatives with clear ROI and benefit tracking.
- Conduct research on emerging AI technologies, including GenAI, RAG, vector search, and evaluation frameworks, to guide practical adoption.
- Translate business problems into AI solution designs, ensuring data readiness and ethical considerations.
- Lead PoCs with defined success criteria and scale successful pilots into production using MLOps/LLMOps practices.
- Partner with business units to embed AI into processes and ensure adoption through enablement and change management.
- Identify opportunities for AI-driven optimization, such as predictive analytics and generative solutions for knowledge work.
- Develop reusable AI components, prompt libraries, and playbooks to accelerate delivery.
- Monitor AI solution adoption using telemetry and feedback loops; continuously improve post-deployment.
- Implement model observability, including drift detection, hallucination monitoring, latency, and cost metrics.
- Maintain a value ledger with KPIs and FinOps metrics to measure business impact and cost efficiency.
- Facilitate governance ceremonies for intake, risk reviews, and value realization checkpoints.
- Conduct lifecycle reviews, bias testing, and Responsible AI audits for deployed models.
- Establish CI/CD pipelines for models, feature stores, and automated evaluation workflows.
- Enforce Responsible AI principles, privacy by design, and prompt/content safety for GenAI solutions.
- Manage incident response for AI pipelines, including rollback and root cause analysis.
- Design observability dashboards covering model quality, adoption, cost, and compliance metrics.
- Build AI productization business cases with TCO, compliance costs, and time-to-value considerations.
- Promote AI literacy, safe usage, and Responsible AI practices across the organization.
Key Skills
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