AI/LLM Application Architect
Core
Lead the architecture, governance, and technical strategy of a controlled AI Harness platform for medical-device R&D, enabling AI-assisted quality and engineering workflows.
Role type
Senior IC AI/LLM Application Architect
Builds
Enterprise AI R&D Quality Management System (QMS) Harness
Domain
Medical device R&D / Regulated Quality Systems
Deliverable
production ML models
Required skills
AI/LLM application architecture, RAG systems, prompt and model governance, API integration, secure enterprise system design, audit-ready solution design, Python, human-in-the-loop workflows, regulated development frameworks (ISO 13485, IEC 62304, ISO 14971, FDA 21 CFR Part 820/11)
Preferred skills
Medical imaging, QMS tooling, DHF workflows, regulated engineering environments
Technologies
Azure OpenAI, AWS Bedrock
Responsibilities
Lead end-to-end architecture of the AI R&D QMS Harness including enterprise data access, knowledge/RAG layers, and audit logging; Define system boundaries, approved data classes, model whitelisting, and human-in-the-loop controls; Design and govern core AI agents for Requirement Quality, Traceability, DHF/Evidence, and Risk workflows; Translate business and QMS requirements into scalable, secure, and validated application architecture; Establish technical controls for source citation, RBAC, version control, and reproducibility; Partner with QA, RA, Risk, and Validation teams to define AI Use SOPs and validation evidence; Lead technical qualification of AI use cases through URS, OQ, PQ, and regression testing; Define the target operating model for AI/LLM development and deployment strategy; Evaluate model providers, orchestration frameworks, and deployment options for cloud and local inference.
Seniority
Senior, hands-on IC