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.

This is a remote position.