AI Architect (6 months contract)

Contract duration: 6 months (with a potential extension)

Engagement Type: Full-time

Start date: July 2026

Location: Abu Dhabi (on-site)

Role Overview

We are seeking an experienced AI Architect to define how we design, secure, and scale AI across the organization. You’ll translate business strategy into reference architectures, platform decisions, and guardrails that engineering teams execute against — balancing capability, cost, risk, and time-to-value.

Where AI Engineers ship features, you’ll shape the platform: model strategy, the data and retrieval foundation, the LLMOps backbone, the security posture, and the governance model. Increasingly, that means architecting agentic systems, multi-model routing, and responsible AI controls that comply with regulations like the EU AI Act.

Key Responsibilities

• Define AI strategy and reference architectures for generative AI, agentic systems, RAG, and predictive ML.
• Set model strategy: build‑vs‑buy, open‑weight vs. hosted, multi‑model routing, and a framework for evaluating new models as they ship.
• Architect the data and retrieval foundation — lakehouse, feature stores, vector stores, and lineage — that AI systems depend on.
• Design the LLMOps/MLOps platform: experiment tracking, model and prompt registries, automated eval gates, and observability.
• Lead AI security: threat modeling for prompt injection and data exfiltration, and OWASP LLM Top 10 mitigations.
• Own responsible AI and governance — risk classification, human oversight, auditability, and alignment with the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
• Establish FinOps for AI: cost models, token budgeting, and unit economics per use case.
• Provide technical leadership, review designs, mentor engineers, and align stakeholders from engineering to the executive team.

Candidate Requirements

• 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.
• Bachelor's or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
• 8+ years in software/data engineering, with 3+ years architecting AI/ML or large‑scale data systems.
• A track record of designing and delivering production AI systems end‑to‑end, ideally including GenAI/LLM workloads.
• Deep understanding of LLM and ML system design — RAG, agents, fine‑tuning trade‑offs, evaluation, serving, and the full MLOps/LLMOps lifecycle.
• Strong cloud architecture skills (Azure, AWS, or GCP) plus a modern data platform (Databricks or Snowflake).
• Expertise in AI security, responsible AI, and data governance, with awareness of relevant regulations.
• Excellent communication — able to influence both engineers and executives.
• Hands‑on enough to prototype, review code, and earn engineering teams’ trust.

Nice to have

• Architecting AI for regulated or sovereign environments (finance, healthcare, government, GCC/UAE).
• Enterprise architecture frameworks (TOGAF) and well‑architected reviews.
• Defining golden‑path tooling for internal AI development.
• Running structured vendor PoCs and bake‑offs.

Tools & Technologies You’ll Work With

• Patterns: RAG, agentic/multi‑agent, event‑driven, lakehouse/medallion; reusable blueprints.
• Model strategy: multi‑model routing and gateways (LiteLLM, Portkey); Claude, GPT, Gemini, Llama, Mistral.
• Platforms: Azure AI Foundry, AWS Bedrock, Vertex AI, Databricks Mosaic AI.
• Data foundation: Delta Lake/Databricks, Snowflake, Unity Catalog, vector stores, knowledge graphs.
• LLMOps/MLOps: MLflow, LangSmith/Langfuse, model and prompt registries, eval‑in‑CI.
• Security & governance: OWASP LLM Top 10, NIST AI RMF, ISO/IEC 42001, EU AI Act, RBAC/ABAC, secrets management.
• Infra & observability: Kubernetes, Terraform/OpenTofu, OpenTelemetry; token/cost dashboards.