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.