AI Engineer

Contract duration: 6 months (with a potential extension)

Engagement Type: Full-time

Start date: July 2026

Location: Abu Dhabi (on-site)

We are seeking an experienced AI Engineer to design, build, and deploy production-grade AI systems — primarily LLM-powered applications, RAG pipelines, and agentic workflows — that solve real client business problems in the UAE. The role combines applied AI expertise with solid software and data engineering foundations, with hands‑on ownership from prototype to production and hypercare.

• Design and deliver end-to-end LLM applications: scope the use case, build, evaluate, deploy, and hand over reliable, observable services.
• Build and optimize RAG pipelines: data parsing, ingestion, chunking, embeddings, vector search, re‑ranking, and context-window optimization.
• Design and orchestrate agentic workflows for reasoning, planning, and task execution.
• Build evaluation and observability: define metrics (accuracy, latency, cost-per-task), run eval pipelines, and monitor systems in production.
• Integrate AI components into client applications via secure backend APIs; collaborate with data, software, and Dev Sec Ops  teams.
• Engineer the supporting data layer: pipelines, feature/embedding stores, and data quality for AI workloads on cloud platforms.
• Manage the full lifecycle: deployment, monitoring, versioning, rollback readiness, and cost/performance optimization.
• Translate business problems into AI solutions and communicate model capabilities, limitations, and trade‑offs clearly to clients and stakeholders.
• Maintain technical documentation, runbooks, and delivery artifacts across Design & Align → Build → UAT → Production & Hypercare.

• Demonstrated experience delivering AI solutions in an enterprise or client-facing/consulting environment.
• Prior experience at management consulting firms and/or Big Tech is an advantage.
• Strong Python and solid software engineering fundamentals.
• Hands‑on LLM APIs (Anthropic, OpenAI, Azure OpenAI), including tokenization, latency, and cost control.
• Proven RAG architecture experience with vector databases (e.g., Azure AI Search, Qdrant, Chroma, Pinecone, FAISS).
• Experience with agent/orchestration frameworks (e.g., Lang Chain, Lang Graph, CrewAI).
• Evaluation and observability skills for production AI (eval pipelines, LLM‑as‑judge, monitoring).
• Working knowledge of a major cloud AI/data stack (Azure, AWS, or GCP) and MLOps tooling (e.g., MLflow, Docker).
• Solid data engineering skills: SQL, distributed processing (e.g., Spark/Databricks).
• Strong collaboration and communication skills — able to work with both technical teams and senior client stakeholders.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 3–6 years of experience building and shipping AI/ML solutions into production.
• Preferred certifications (nice to have): cloud AI certifications (Azure AI Engineer, AWS ML, Databricks GenAI Engineer).