Sr AI Engineer

Job summary

Key responsibilities

• Design, develop, and deploy AI/ML solutions for enterprise business requirements.
• Build generative AI applications with open-source and commercial LLMs, including Llama, Mistral, and Hugging Face models.
• Develop agentic AI solutions, autonomous workflows, and multi-agent systems.
• Build RAG pipelines using embeddings, vector databases, semantic search, and reranking.
• Implement orchestration with LangGraph, LangChain, AutoGen, or similar frameworks.
• Fine-tune, evaluate, and optimize models for enterprise use cases.
• Design secure, scalable AI architecture integrated with applications, APIs, databases, and business systems.
• Develop and deploy AI services using Python, ML frameworks, APIs, and microservices.
• Implement evaluation, performance metrics, monitoring, regression detection, and quality assurance.
• Optimize inference, latency, scalability, and resource use; apply MLOps for deployment, versioning, and monitoring.
• Ensure security, privacy, AI governance, and responsible AI compliance; collaborate with technical teams and stakeholders.

Required skills and qualifications

• 7+ years of professional AI/ML engineering or related experience.
• At least 3 years of hands-on generative AI, LLM, and agentic AI experience.
• Strong Python skills and experience with PyTorch, TensorFlow, and Scikit-learn.
• Practical experience with open-source models and frameworks, including Hugging Face Transformers, Llama, or Mistral.
• Knowledge of LLM architecture, prompt engineering, fine-tuning, embeddings, and inference optimization.
• Hands-on RAG, vector search, reranking, and retrieval optimization experience.
• Experience with AI agents and multi-agent systems using LangGraph, LangChain, AutoGen, or equivalents.
• Knowledge of enterprise architecture, integration, microservices, APIs, scalability, and security.
• Experience in model evaluation, observability, monitoring, and regression testing.
• Familiarity with Docker, Kubernetes, CI/CD, cloud infrastructure, and MLOps.
• Experience deploying and maintaining production AI applications.
• Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or a related discipline; Bachelor's is also listed as required.

Preferred skills

• Vector database experience with Qdrant, Milvus, Weaviate, or Pinecone.
• Experience with vLLM or Ollama serving frameworks.
• Knowledge of Azure, AWS, or Google Cloud AI infrastructure.
• GPU deployments, model quantization, and performance optimization experience.
• Familiarity with enterprise AI governance, identity management, and secure data integration.

Key competencies

• Machine learning and deep learning; generative AI and LLMs; open-source models and fine-tuning.
• Agentic AI and multi-agent systems; RAG, embeddings, vector search, and reranking.
• LangGraph, LangChain, and AutoGen; enterprise AI architecture and integration.
• AI evaluation, monitoring, and MLOps.

Location and work arrangement

• Muscat, Oman; onsite and in person.