Domain AI Azure Architect

Role Description

We are currently searching for a AI Azure Architect :

• Design and implement end-to-end AI architecture for a new product within Technology Risk, focused on SOC reporting and intelligent automation.
• Lead the design and development of AI/ML architecture, including LLM-based solutions, model orchestration, and intelligent workflows.
• Develop scalable, API-first architectures to integrate LLMs and expose AI capabilities across enterprise platforms and systems.
• Define and govern AI models, pipelines, and infrastructure across cloud environments (Azure, AWS, GCP), ensuring scalability, security, and compliance with enterprise and regulatory standards.
• Establish frameworks and best practices for prompt engineering, model fine-tuning, evaluation, monitoring, AI governance, explainability, and responsible AI.
• Lead the integration of structured and unstructured data into AI pipelines.
• Collaborate with cross-functional teams (technologists, data specialists, and business stakeholders) to translate business requirements into AI-driven solutions.
• Provide technical leadership in resolving complex architecture challenges and drive product innovation by embedding automation and intelligence into workflows.

Qualifications

• Strong experience in AI/ML architecture, enterprise-grade solution design, and distributed scalable architectures.
• Proven hands-on experience working with Large Language Models (LLMs), generative AI, and AI platforms (e.g., GPT-like models, prompt engineering, fine-tuning).
• Experience designing and integrating APIs and microservices for scalable AI ecosystems.
• Hands-on Cloud experience with Azure (preferred), AWS, or GCP.
• Familiarity with vector databases, embeddings, and semantic search, alongside an understanding of structured/unstructured data processing.
• Knowledge of AI ethics, bias mitigation, model explainability, and Responsible AI governance.
• M.S. or B.S. in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Requirements

• Strong experience in AI/ML architecture and solution design.
• Proven experience working with LLMs, generative AI, and AI platforms.
• Experience designing and integrating APIs and microservices.
• Cloud experience: Azure (preferred), AWS, or GCP.
• Familiarity with vector databases, embeddings, and semantic search.
• Understanding of Tech Risk, compliance, or SOC-related processes (preferred).
• Experience in distributed systems and scalable architectures.
• M.S. or B.S. in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.

Benefits

• Flexible work arrangement: Remote.