Job overview
Date posted
15/09/2025
Location
Muscat, Oman
Salary
Undisclosed
Compensation
Comprehensive package + relocation
Experience
5 - 10 yrs
Seniority
Senior & Lead
Qualification
Bachelors degree
Expiration date
30/10/2025
Job description
The Proficient, AI (COE) role at Omantel is responsible for managing and governing the discovery, delivery, and governance of enterprise AI initiatives across the organization. The position ensures AI adoption is outcome-driven, responsibly governed, secure, and scalable. The role includes leading use-case portfolio management, incubating solutions, overseeing MLOps/LLMOps practices, and realizing business value through measurable KPIs. It involves driving AI solution design, establishing governance frameworks, conducting Responsible AI audits, and embedding AI into core business processes to achieve adoption and efficiency gains.
Required skills
business strategy
business analysis
automation
ai governance
use case portfolio management
mlops
llmops
genai
rag
vector search
predictive analytics
model observability
ci cd pipelines
bias testing
responsible ai
data readiness
feature stores
ai solution design
finops metrics
ai productization
Key responsibilities
- 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.
- 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.
- Develop reusable AI components, prompt libraries, and playbooks to accelerate delivery.
- Monitor AI solution adoption using telemetry and feedback loops.
- 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.
Experience & skills
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; advanced degree preferred.
- Certifications in cloud AI/ML such as Azure AI Engineer, AWS Machine Learning, Google Professional ML Engineer, or Responsible AI are a plus.
- 7–9 years of experience in AI, ML, or related technology strategy roles.
- Experience in use-case portfolio management, MLOps/LLMOps, and AI governance.
- Proficiency in AI solution design including GenAI, RAG, vector search, and predictive analytics.
- Proven track record of conducting Responsible AI audits, bias testing, and lifecycle reviews.
- Ability to establish CI/CD pipelines for models, feature stores, and automated workflows.
- Strong understanding of FinOps metrics and AI productization business cases.
- Knowledge of model observability including drift detection and cost monitoring.
- Excellent communication, stakeholder engagement, and change management skills.