Define the technical architecture for the company's AI solutions, including selection of approaches, models, frameworks and platforms
Participate in design decisions for transformational AI projects, assessing technical feasibility, risks and strategic alignment
Establish corporate standards for model development, deployment, monitoring and governance (including generative AI)
Critically evaluate vendor and partner proposals, identifying technical risks, dependencies and gaps
Collaborate with the Data Architect to ensure that infrastructure and data standards support AI project requirements
Map implications for explainability, auditability and reliability of models in regulated contexts

Experience designing and implementing machine learning and generative AI solutions in production environments
Proficiency in architecture patterns for AI systems: RAG, fine-tuning, agents, LLM orchestration
Knowledge of cloud AI platforms (Azure OpenAI, AWS Bedrock, Vertex AI or similar)
Familiarity with MLOps and practices for monitoring models in production
Ability to assess technical risks of AI solutions: hallucination, drift, bias, vendor dependency

Preferred qualifications

Experience in regulated industries, especially energy or financial services
Knowledge of AI governance and responsible AI frameworks (e.g., NIST AI RMF, ISO 42001, AI Act)
Experience integrating AI systems with legacy mission-critical systems
Experience with regulatory approval processes involving automated decision systems

Solutions Architect, AI

Key skills