AI Architect

About the role

The AI Architect defines and governs enterprise‑wide artificial intelligence architecture, ensuring secure, scalable and business‑aligned adoption of AI, machine learning, generative AI and large language model solutions across transformation initiatives.

Key responsibilities

• Develop and maintain enterprise AI architecture aligned with business strategy, data strategy and digital transformation goals.
• Define target‑state AI architecture, transition roadmaps, principles, standards, reference architectures and governance guardrails.
• Design architectures for machine learning, deep learning, generative AI, LLMs, intelligent automation and AI‑enabled applications.
• Specify AI platform architecture covering development, training, deployment, inference, monitoring and lifecycle management.
• Embed responsible AI, privacy, security, explainability and fairness requirements into all designs.
• Collaborate with enterprise, data, integration, cloud, security and solution architects to ensure coherent end‑to‑end solutions.

Required profile

• 8‑10 years of experience in technology, data, software engineering, analytics or related fields, with at least 3‑5 years focused on AI/ML architecture.
• Proven track record designing enterprise‑scale AI, machine‑learning or generative AI solutions and supporting transformation programs.
• Strong analytical, systems‑thinking and stakeholder‑management capabilities, with ability to translate business opportunities into governable AI architectures.

Required skills

• Cloud AI services on Microsoft Azure, Amazon Web Services or Google Cloud.
• Machine‑learning frameworks such as PyTorch, TensorFlow and scikit‑learn.
• MLOps/LLMOps platforms and model lifecycle management tools.
• Vector databases, semantic search and Retrieval‑Augmented Generation technologies.
• Containerization and orchestration tools like Docker and Kubernetes.
• Enterprise architecture tools (e.g., Bizzdesign, Sparx Enterprise Architect, Orbus/iServer, ARIS).