Enterprise Architect (AWS, Data. AI)

An AI Enterprise Architect defines, designs, and governs the overarching strategy, infrastructure, and standards for adopting Artificial Intelligence across an organization . This role bridges business objectives with technical AI capabilities (machine learning, LLMs, data pipelines) to ensure secure, scalable, and compliant AI implementations. They build AI reference architectures, manage AI platforms (e.g., MLOps), and ensure alignment with data governance and IT security.

Key Responsibilities

• Strategy & Roadmap: Define the target state architecture for AI, identifying opportunities to improve business processes through AI/ML technologies.
• Architecture Design: Create, maintain, and publish AI reference architectures, standards, and patterns for AI development and deployment.
• Platform & Data Governance: Build POC and help scaling AI platforms (LLMOps, RAG frameworks) while establishing governance for AI ethics, security, privacy, and compliance.
• Technical Leadership: Partner with data scientists, engineers, and stakeholders to translate business needs into actionable, high-performance AI solutions.
• Technology Evaluation: Assess emerging AI technologies and vendors, leading technical evaluations to close capability gaps.

Qualifications & Skills

• Experience: 10+ years in enterprise/solution architecture, with 3+ years specifically in AI/ML, data platform architecture, or AI-driven application development.
• Technical Knowledge: Proficiency in Typescript / Python, SQL, cloud platforms (AWS, Azure, Google Cloud Platform), machine learning frameworks, data engineering, and containerization/orchestration.
• AI Specialization: Strong understanding of Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and Model Operations (MLOps). MCP server.
• Agent Platform : Langchain, Crew AI, Azure AI foundry (at least one of them)
• Communication: Ability to articulate complex AI concepts to non-technical stakeholders and influence senior management.
• Frameworks: Knowledge of EA frameworks (TOGAF), ITIL/COBIT for governance, and Agile methodologies.