Senior AI Engineer

We're hiring a Senior AI Engineer to design, build, and ship ML and LLM-powered products and the infrastructure behind them. You'll work across the full stack — from data pipelines and model fine-tuning through backend services and MLOps — and play a lead role in shaping how AI systems are built and operated across the organization. This is a hands-on senior role with technical ownership and direct influence on AI products reaching enterprise and government customers.What You'll DoDesign and implement production-grade ML and LLM applications: RAG pipelines, fine-tuning workflows, evaluation frameworks, and inference services.Fine-tune open-source LLMs (e.g., Llama, Mistral, Qwen) using techniques such as LoRA/QLoRA, SFT, and DPO for domain-specific use cases.Build and operate the backend services that power our AI products — APIs, orchestration layers, async job processing, and integrations.Own MLOps practices: CI/CD for models, experiment tracking, model registry, monitoring, drift detection, and cost/performance optimization.Design and maintain data engineering pipelines that ingest, clean, transform, and serve structured and unstructured data to AI systems (text, PDF, audio, video).Build evaluation and observability tooling for LLM outputs (offline benchmarks, online metrics, human-in-the-loop feedback loops).Collaborate with product, data, and infrastructure teams to translate business problems into deployable AI solutions.Mentor junior engineers, set technical standards, review code and architecture, and contribute to hiring.Required Qualifications5+ years of professional software engineering experience focused on AI/ML or LLM systems in production.Strong NLP and LLM fine-tuning experience: hands-on work with Hugging Face Transformers, PEFT/LoRA, dataset curation, evaluation, and deployment of fine-tuned models.MLOps background: model versioning, experiment tracking (MLflow, Weights & Biases, or similar), containerization (Docker), orchestration (Kubernetes), and CI/CD for ML workloads.Full-stack engineering with backend focus: strong Python (FastAPI, Django) and proficiency building scalable APIs, async workers, and event-driven services.Data engineering fundamentals: SQL and NoSQL databases, vector databases (pgvector, Qdrant, Weaviate, or Milvus), ETL/ELT pipeline design, and stream/batch processing.Experience with cloud platforms (AWS, Azure, or GCP) and on-premises GPU environments.Excellent communication skills in English; ability to work directly with technical and non-technical stakeholders.Nice to HaveExperience building AI agents and multi-agent systems.Voice AI experience: ASR (Whisper, conformer-based models), TTS, voice agent pipelines.Computer vision experience: detection, OCR, document understanding, or multimodal models.Classical ML expertise: XGBoost, scikit-learn, feature engineering, and tabular modeling.Deep learning frameworks: PyTorch (preferred), TensorFlow.Data versioning and pipeline tooling: DVC, LakeFS, Airflow, Prefect, Dagster, or Kubeflow Pipelines.LLM observability and tracing tools (LangFuse, Langsmith, Arize, Helicone).Arabic NLP experience or familiarity with localization challenges in the region.Contributions to open-source AI/ML projects or relevant publications.