Permitting Manager

Position Objectives:

  • To manage and coordinate all permitting activities required for network construction projects, ensuring timely approvals from local authorities and full compliance with regulatory and environmental requirements.

Job Description & Responsibilities:

  • Manage the end-to-end permitting process for civil and network infrastructure projects.
  • Liaise with government agencies, municipalities, and utility companies to secure necessary approvals.
  • Prepare and submit permit applications, drawings, and supporting documents.
  • Track and follow up on permit status to ensure timely issuance.
  • Maintain a permit database and documentation records for all projects.
  • Coordinate with design and construction teams to align project schedules with permit timelines.
  • Ensure compliance with local laws, environmental regulations, and safety standards.
  • Identify and mitigate potential permitting risks and delays.
  • Build and maintain strong working relationships with regulatory authorities and stakeholders.
  • Provide regular permit status reports to project management and leadership

Qualifications & Experience:

  • Bachelor’s degree in civil engineering.
  • Minimum 10 years of telecommunication experience in OSP design and engineering positions.
  • Must know OSP work, related processes and industry best practices
  • Must have working knowledge of market-leading OSP design tools (Hexagon, Intergraph, or similar).
  • Excellent knowledge of the English language
  • Must have international experience from developed markets.
Al Mohammadiyyah, Saudi Arabia
Ooredoo

GenAI Engineer

Position Objective:

  • Deliver practical Generative AI solutions by converting ideas into production-ready systems.
  • Balance rapid prototyping with solid engineering practices and scalability.
  • Design, implement, and optimize LLM and RAG-based pipelines.
  • Build and expose APIs for seamless integration with applications.
  • Deploy and manage services on Kubernetes/OpenShift with GPU orchestration.
  • Ensure observability, monitoring, and cost-efficient performance of AI services.
  • Collaborate with cross-functional teams to deliver impactful, end-to-end AI solutions.


Job Description & Responsibilities:

  • Design, implement, and optimize Generative AI solutions using LLMs and RAG pipelines.
  • Convert prototypes into robust, production-ready services with scalability in mind.
  • Build, document, and expose APIs for seamless integration across applications.
  • Package, deploy, and manage AI services on Kubernetes/OpenShift with GPU support.
  • Develop evaluation harnesses to benchmark quality, latency, and cost across models.
  • Integrate observability, logging, and monitoring into deployed AI systems.
  • Collaborate with MLOps, Data Engineering, and Application teams for end-to-end delivery.
  • Apply best practices in system design, performance optimization, and cost efficiency.
  • Debug and resolve issues in AI models, pipelines, and deployments.
  • Stay updated with emerging GenAI tools, frameworks, and industry practices.
  • Ensure timely delivery of prototypes, iterations, and final solutions.
  • Translate business requirements into usable and impactful AI applications.


Qualifications & Experience:

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
  • Minimum 3+ years of professional experience in AI/ML and Generative AI application development.
  • Proven track record of designing, implementing, and productionizing LLM and RAG-based solutions.
  • Strong experience with MLOps practices, including CI/CD pipelines for AI models and services.
  • Expertise in containerization and orchestration (Kubernetes, OpenShift, Docker) with GPU management.
  • Hands-on coding experience in Python with frameworks such as FastAPI, LangChain, PyTorch, TensorFlow, Hugging Face.
  • Practical knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus).
  • Familiarity with cloud AI services (AWS Sagemaker, Azure OpenAI, Google Vertex AI) for scalable deployments.
  • Strong background in API development, system integration, and microservices architecture.
  • Experience in observability tools (Prometheus, Grafana, ELK stack) and AI service monitoring.
  • Ability to benchmark models for quality, latency, throughput, and cost efficiency.
  • Exposure to enterprise-level AI deployments in regulated or large-scale environments is a plus.
Al Mohammadiyyah, Saudi Arabia
SPPC