AI Engineer – LLM Platform & Cloud Operations

About the role

We are looking for an experienced AI Engineer to design, build, and operate large‑language‑model (LLM) systems at scale. You will translate business use cases into production‑ready AI services, lead a cloud‑focused AI operations team, and ensure robust, secure, and observable deployments.

Key responsibilities

• Build, fine‑tune, and evaluate LLMs (e.g., Llama‑3, Mistral) using QLoRA/PEFT on GPU clusters.
• Design reproducible evaluation harnesses, A/B testing frameworks, and safety guardrails.
• Architect multi‑agent and Retrieval‑Augmented Generation (RAG) pipelines with LangGraph, FastAPI, and vector databases.
• Design, provision, and manage cloud infrastructure (Azure, OCI, GCP) for AI workloads on Kubernetes, Docker/Podman, and Terraform.
• Implement CI/CD pipelines, GitOps release models (Argo CD), and end‑to‑end observability (Azure Monitor, Application Insights, ELK).
• Lead and mentor a cloud/AI operations team, standardize SDLC practices, and drive platform consolidation.
• Own disaster‑recovery design, security baselines, and compliance for large‑scale national digital platforms.

Required profile

• Bachelor’s degree in Software Engineering, Computer Science or related field.
• 6–8+ years of software, DevOps, or platform engineering experience, including at least 2 years in applied AI/ML.
• Proven delivery of production AI/LLM systems.
• Experience leading engineering teams and setting standards across multiple squads.
• Professional proficiency in English (Arabic optional).

Required skills

• Python, Bash, YAML
• Kubernetes, Docker, Podman, Terraform
• Azure (preferred), OCI, GCP
• Azure DevOps, GitHub Actions, Argo CD
• CI/CD at scale, GitOps release models
• QLoRA/LoRA, PyTorch, Transformers
• LangGraph, FastAPI
• Vector databases: Milvus, Pinecone, Weaviate
• Observability tools: Azure Monitor, Application Insights, ELK
• Security & compliance tools: SonarQube, Black Duck