GENERATIVE-AI ENGINEER (OMANI NATIONAL)
On-siteMuscat, Muscat, Oman
Job Summary
Build RAG-based GenAI solutions for enterprise use cases by developing Python-based services and APIs that integrate LLMs. Support data preprocessing, embeddings, and retrieval pipelines while contributing to model deployment and integration tasks. Debug and improve existing pipelines under supervision, working closely with senior engineers to address production constraints regarding latency, cost, and accuracy. Assist in building these systems with a focus on hands-on implementation, integration, and learning-by-delivery. This early-career role supports the development of Generative AI solutions including LLMs and RAG systems for the Omani National team.
Required Qualifications
- Python (Strong)
- Model Packaging & Deployment (Strong)
- RAG Workflow (Strong)
- Prompt Engineering with LLMs (Strong)
- Strong foundation in Python (data handling, APIs, scripts)
- Understanding of APIs, Docker, or deployment workflows
- Exposure to deploying ML/AI models (even in projects/internships)
- Understanding of embeddings, retrieval flow
- Hands-on exposure through projects
- Experience working with GPT/Llama APIs
- Ability to structure prompts and evaluate outputs
- Vector Databases (Exposure Level) - Familiarity with FAISS / Chroma / Pinecone and basic usage in projects
- ML Fundamentals: Core concepts - overfitting, evaluation metrics, basic algorithms
- Ability to reason about model behavior
- Bachelor's in Computer Science / Data Science or related field
- 12 years of experience in AI/ML (including internships and project work)
- Exposure to at least one end-to-end ML/GenAI project (academic and professional)
Desired Qualifications
- Vector Databases and Embeddings (Capable)
- LangChain / LlamaIndex exposure
- Cloud basics (Azure / AWS / GCP)
- Basic understanding of CI/CD or MLOps concepts
- Internship/project experience in GenAI or ML use cases
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