AI Engineer

Job description

Build, fine-tune, and evaluate large language models for domain-specific tasks. Design reproducible evaluation harnesses and A/B test frameworks with tracked metrics. Architect multi‑agent and Retrieval‑Augmented Generation systems from prototype to production. Implement safety guardrails for input/output validation and policy enforcement. Translate business use cases into deployable prototypes and demo them to stakeholders. Design and operate cloud infrastructure and MLOps workspaces on Kubernetes and container runtimes. Build CI/CD pipelines and GitOps releases across development, test, and production environments. Implement end‑to‑end observability and incident response. Lead a cloud/AI operations team and define monitoring, incident response, and release governance practices.

Requirements

• Bachelor's degree in Software Engineering, Computer Science, or related field
• 6–8+ years in software, DevOps, or platform engineering
• at least 2 years in applied AI or ML engineering
• proven delivery of production AI/LLM systems
• strong Python proficiency
• comfortable with Bash and YAML
• deep hands‑on experience with Kubernetes, Docker/Podman, and Terraform
• production experience with a major cloud (Azure preferred
• OCI or GCP acceptable)
• demonstrated ownership of CI/CD at scale (Azure DevOps or GitHub Actions) and GitOps release models
• experience leading a team and setting engineering standards
• Master's degree in Applied AI, Machine Learning, or related discipline (preferred)
• fine‑tuning experience with QLoRA/LoRA on GPU clusters using PyTorch and Transformers
• vector database experience (Milvus, Pinecone, or Weaviate) and RAG design
• experience delivering Saudi government or large‑scale national digital platforms with local compliance knowledge
• professional proficiency in Arabic and English.

Skills