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.

This is a remote position.