AI Architect

AI Architect

We are seeking a senior AI Architect to lead the design and development of enterprise AI capabilities across a healthcare and cancer research organization. This role will define the architecture, standards, and roadmap for Generative AI, machine learning, enterprise search, RAG, AI assistants, and agentic AI.

Key Responsibilities

• Define enterprise AI architecture, standards, reference designs, and technology roadmap.
• Architect Generative AI, LLM, RAG, semantic/vector search, AI assistant, and agentic AI solutions.
• Design secure integrations between AI platforms, enterprise applications, APIs, knowledge repositories, and data platforms.
• Establish reusable AI services, model-selection patterns, guardrails, evaluation, monitoring, and human-in-the-loop controls.
• Define standards for MLOps/LLMOps, deployment, model lifecycle management, and monitoring.
• Partner with data, cloud, security, clinical, research, and application teams to move AI solutions into production.
• Ensure AI solutions meet requirements for security, privacy, governance, auditability, and responsible AI.
• Provide technical leadership and communicate architecture, risks, and technology decisions to senior stakeholders.

Required Skills

• 10+ years in enterprise architecture, solution architecture, data/cloud architecture, software engineering, AI/ML, or related disciplines.
• Strong enterprise architecture experience with Generative AI and LLM-based platforms.
• Strong knowledge of:
  • LLMs and Generative AI
  • RAG and enterprise search
  • Embeddings and vector databases
  • AI agents / agentic workflows
  • APIs and enterprise integrations
  • Cloud AI platforms
  • MLOps / LLMOps
• Strong understanding of modern data architecture, cloud platforms, APIs, containers/Kubernetes, and distributed systems.
• Experience designing solutions involving sensitive or regulated data.
• Knowledge of AI security, privacy, governance, model risk, and responsible AI.
• Strong technical leadership and executive communication skills.

Preferred

• Experience with Glean or similar enterprise AI search / knowledge-management platforms.
• Healthcare, life sciences, cancer research, pharmaceutical, or other regulated-industry experience.
• Familiarity with FHIR, HL7, DICOM, Epic, or clinical/research data environments.
• Experience with Azure, AWS, or Google Cloud AI platforms.
• Experience with enterprise RAG platforms, vector databases, knowledge graphs, model gateways, or agent frameworks.

Ideal Candidate

A senior architect who combines enterprise architecture leadership with hands-on technical depth in GenAI, RAG, LLMs, agents, cloud/data architecture, and AI governance.