10+ years in enterprise or solution architecture, with 3+ years in AI/ML specifically.
Proficiency in Typescript, Python, SQL, and cloud platforms like AWS, Azure, or GCP.
Strong understanding of Large Language Models (LLMs), Generative AI, and Model Operations (MLOps).
Experience with AI agent platforms, such as Langchain or Azure AI Foundry.
Ability to communicate complex AI concepts to non-technical stakeholders effectively.
Familiarity with EA frameworks (TOGAF), ITIL/COBIT, and Agile methodologies.
Responsibilities
Define the target state architecture for AI to enhance business processes with AI/ML technologies.
Create and maintain AI reference architectures, standards, and deployment patterns.
Build proofs of concept and scale AI platforms while ensuring compliance with ethical, security, and privacy standards.
Partner with data scientists, engineers, and stakeholders to transform business needs into high-performance AI solutions.
Evaluate emerging AI technologies and vendors to address capability gaps.
Benefits
Opportunity to influence AI strategy at an organizational level.
Collaboration with a diverse team of AI professionals and stakeholders.
Access to cutting-edge AI tools and platforms.
Growth and development opportunities in the rapidly evolving AI landscape.
Full Job Description
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, GCP), 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.
