Lead AI Solutions Architect for Production-Grade AI

Client of Forsyth Barnes; Dubai; On-site; AED 380,000 - 580,000; Full time

Job summary

Forsyth Barnes in the United Arab Emirates seeks an experienced AI Architect to lead the architectural design and delivery of production AI/ML solutions for enterprise problems. You will define solution blueprints and select models and tooling, and drive integrations with cloud services and enterprise applications to ensure reliability and compliance.

Partner with product managers, engineering teams and data scientists to prioritise work, de-risk delivery and accelerate time to value while

Qualifications

• Experience designing and delivering production AI/ML solutions in enterprise environments.
• Strong knowledge of cloud platforms and selecting services for compute, storage, and deployment of ML models.
• Hands-on experience with MLOps, model monitoring tools, feature stores or model registries.

Responsibilities

• Own end-to-end solution architecture for AI initiatives from requirements through to deployment and operational handover.
• Define model integration patterns data pipelines and inference infrastructure tuned for performance and cost.
• Drive cross-functional design workshops to align stakeholders on scope constraints and success criteria.
• Produce architecture artefacts including diagrams interfaces and non-functional requirement specifications.
• Evaluate and recommend cloud services frameworks and tooling to meet security compliance and scalability needs.
• Establish practices for model governance monitoring retraining triggers and observability.
• Conduct technical reviews code and design reviews and mentor engineering and data science teams.
• Support proof-of-concept work to validate approaches and rapidly iterate on promising directions.

Job description

Forsyth Barnes in the United Arab Emirates seeks an experienced AI Architect to lead the architectural design and delivery of production AI/ML solutions for enterprise problems. You will define solution blueprints and select models and tooling, and drive integrations with cloud services and enterprise applications to ensure reliability and compliance.

Partner with product managers, engineering teams and data scientists to prioritise work, de-risk delivery and accelerate time to value while