Artificial Intelligence Engineer

Description:

Technical Skills:

* 7+ years in software engineering, with 4+ years in AI/ML engineering or MLOps in production environments.

* Expert in both C# (.NET Minimal APIs) and Python (FastAPI, LangChain, LlamaIndex, PyTorch)—with deep experience writing testable, observable, and maintainable backend services.

* Proven track record building AI microservices on Kubernetes, with GPU scheduling, service mesh (Istio/Linkerd), and infrastructure-as-code (Helm/Terraform).

* Hands-on experience deploying on-prem LLM inference stacks (vLLM, TGI, Triton) and replicating cloud/NVIDIA NIM patterns in private data centers.

* Strong grasp of MLOps fundamentals: model/prompt/dataset versioning, CI/CD for AI, shadow/canary deployments, drift detection, and SLO-driven alerting.

* Experience with RAG systems: embedding models (Qwen, Jina), vector DBs (Qdrant, FAISS), rerankers (ColBERT), and retrieval evaluation (hit-rate, RAGAS).

* Familiarity with evaluation-by-design: automated scoring (grounding, safety, parity), human-in-the-loop validation, and threshold-based promotion gates.

* Understanding of security & compliance: zero-trust networking, PII handling, auditability, and risk tiered governance.

* Excellent algorithmic thinking, system design skills, and a performance-first mindset (latency, throughput, cost per request).

Preferred Qualifications:

* Experience fine-tuning Arabic LLMs (AraBERT, Qwen-Arabic) or working with Gulf dialects.

* Contributions to open-source AI tooling or MLOps platforms. Knowledge of .NET for AI scenarios (e.g., ML.NET, gRPC interop with Python services).

* Exposure to agent frameworks (LangGraph) and multi-step agentic workflows with tool calling.

* Experience in government, defense, or highly regulated sectors with strict data sovereignty requirements