What Jobs are available for AI Internship in Oman?

We are building AI-native applications that transform messy, real-world data into actionable intelligence. This is a builder's role, you'll work on cutting-edge AI agents, LLM-based systems, and mission-critical applications that directly impact industries like energy, defense, finance, and sovereign data infrastructure.

We need someone who ships fast, learns faster, and thrives with minimal supervision.

• End-to-End AI Systems: Design and deploy AI solutions from prototype to production.
• AI Agents: Build multi-capable agents using state-of-the-art models (GPT-4.1/O3/O4, Claude Opus 4, Gemini).
• RAG Pipelines: Develop advanced Retrieval-Augmented Generation and semantic search workflows.
• LLM Tuning: Fine-tune and deploy open-source LLMs for specialized use cases.
• AI-Native Applications: Build integrations with modern AI developer tools (Cursor, Cline, Claude Code).
• Data Ops: Handle messy real-world data, ETL pipelines, embeddings, and retrieval systems.
• System Reliability: Optimize performance, ensure resilience, and deploy scalable AI-native infrastructure.

• 3 –8 years of proven experience in AI Applications / Systems Engineering / Data Infrastructure.
• Hands-on experience with LangChain, LangGraph, LlamaIndex or equivalent frameworks.
• Expertise with vector databases, embeddings, and semantic search.
• Experience managing real-world messy datasets and ETL workflows.
• Familiarity with Kubernetes, containerization, and cloud/on-prem deployment.
• Excellent communication skills (written & verbal).

Nice to Have

• Experience in multi-agent systems.
• Some background in risk analysis, defense systems, or energy infrastructure.
• Familiarity with AI observability, monitoring, and evaluation frameworks.

Role Purpose
To manage and governing Business Process Management (Design, Improvement and Governance) , Automation requirements & AI use cases across Omantel. This role is key to ensure that AI & automation initiatives are aligned with business goals, delivering measurable value, and being effectively utilized by end-users.

Position Information

• Unit: Strategy and Innovation
• Division: Center of Excellence
• Location: Muscat
• Grade: P5
• Minimum role requirements:
• Qualifications: Bachelor's degree in relevant discipline.
• Experience: A minimum of 7 years' experience.

Key Accountabilities

• Fulfill Business Process demand across the entire organization in terms of Design and/or re-engineer, review and governance
• Gather & govern AI use cases across the entire organization
• Conduct research on emerging AI technologies, trends, and best practices. Analyze how these technologies can be applied to solve business problems.
• Analyze Business Process/ AI related requirements, along with consideration of its relevant supporting data and tracking records
• Identify, evaluate, and prioritize high impact AI use cases across business units.
• Lead proof-of-concept (PoC) initiatives, scaling successful projects into production.
• Work with business leaders & SPOCs to drive AI adoption and measurable business value.
• Identify pain areas, opportunities of improvement, in terms of time reduction, cost saving, waste elimination, without compromising quality
• Suggest opportunities for automation based on best industry practices, brainstorming discussions with unit SPOCs, stakeholders and available Business Process Repository information
• Ensure system adoption and benefit realization take place and report progress to management & CMT frequently.
• Monitor BOT performance & BPM flows and report the progress to CoE management on a weekly basis.
• Calculate the RoI for any process/ AI selected use cases then decide on best potential use cases.
• Conduct regular meetings with CoE & business SPOCs to ensure alignment & continuous engagement
• Continuously Monitor the organization's process & automation/ AI capabilities, identify gaps in both capabilities and resources and suggest improvements

The Role

We are seeking an experienced Al/ML Engineer with strong expertise in deploying and maintaining machine-learning services at scale. The ideal candidate will be responsible for running and enhancing our GPU-powered Al infrastructure, ensuring high performance as user demand grows, and integrating new models and pipelines. This is an urgent requirement — candidates must be ready to join within 15 days. Responsibilities
•Deploy, monitor and maintain production AI/ML services on GPU servers (RunPod).
•Scale GPU infrastructure and load-balancing to meet growing user demand; implement autoscaling and cost controls.
•Optimize inference speed and reliability through batching, quantization, caching and other performance techniques.
•Integrate AI models into existing services as required.
•Enhance our current AI model.
•Build and maintain asynchronous processing and queue systems (Celery/Redis or equivalent).
•Implement safety filters and other guardrails around model outputs.
•Ensure zero-touch operations: automatic startup, model pre-loading, health checks, alerts and automated restarts.
•Expose clean API endpoints and work closely with backend developer for seamless integration with the main application.
•Maintain dashboards for GPU usage, latency, error rates and alerting.
•Document all infrastructure, deployment processes and enhancements clearly for handover and future scaling.

Requirements

Requirements
•2+ years of experience deploying machine-learning models into production environments.
•Strong Python skills and experience with PyTorch/TensorFlow or similar frameworks.
•Proven experience with GPU-based inference, performance tuning and cost optimisation.
•Familiarity with containerisation (Docker) and orchestration (Kubernetes or similar).
•Knowledge of queueing systems and asynchronous processing (Celery/Redis, RabbitMQ, etc.).
•Experience integrating multiple model types into APIs is a plus.
•Proficiency with cloud platforms or specialised GPU providers (RunPod, Lambda, AWS, GCP, Azure).
•Understanding of monitoring and observability tools (Prometheus, Grafana, ELK, etc.).
•Version control (Git/GitHub) and CI/CD familiarity.
•Ability to work independently and take full responsibility of the AI/ML infrastructure in production.

About the company

Hike Tech LLC is an Oman-based technology company dedicated to the creation and management of innovative digital platforms. We are dedicated to building, launching and managing high-quality digital products for users worldwide.

Company Description

Elile AI is revolutionizing autonomous systems with our proprietary platform, ElectrOS, designed to empower critical systems in energy, infrastructure, defense, and industrial operations. By fusing agentic intelligence with deeply integrated platform design, we achieve real-time adaptability, self-awareness, and context sensitivity. Our AI agents operate locally, adhering to zero-trust principles and sovereign-by-design architecture. Since our inception in 2019, we have delivered advanced autonomy, enhancing performance and resilience for our partners. Join us in building self-managing systems that scale intelligently and respond dynamically to their environment.

Role Description

This is a full-time remote role for an Artificial Intelligence Engineer. The AI Engineer will be responsible for developing and implementing AI models, focusing on pattern recognition, neural networks, and natural language processing. Daily tasks include researching advanced machine learning algorithms, coding and testing software, and collaborating with cross-functional teams to integrate AI solutions into existing infrastructure. The role requires constant innovation and staying updated with the latest advancements in AI technology.

Qualifications

• Expertise in Generative AI, LLM and Agentic frameoek
• Strong background in Computer Science and Software Development
• Experience with cloud native applications
• Excellent problem-solving skills and the ability to work independently and remotely
• Proficiency in programming languages such as Python, Java, or C++
• Master's or PhD degree in Artificial Intelligence, Computer Science, or related field
• Experience in deploying AI models in real-world applications is a plus