AI Platform Architect

Roth Staffing is looking for an AI Platform Architect within a medical technologies firm. This is an exciting opportunity to work for a global leader in life‑saving medical devices with a strong corporate culture and competitive pay. Pay Rate: $100.00–$130.00 per hour Location: Onsite, Alameda, CA. Contract: 12‑month Temp/contract role. Role Overview Our client is seeking a forward‑thinking AI Platform Architect to design, build, and operationalize enterprise AI platforms that accelerate innovation across research, clinical development, commercial and corporate functions. This role will lead the architecture and governance of a multi‑platform AI ecosystem, spanning AWS (Bedrock, SageMaker), Databricks (Mosaic AI), Claude for Enterprise, and emerging AI‑native / agentic engineering tools and platforms. The architect will ensure scalable, secure, and compliant deployment of AI capabilities while enabling rapid experimentation and adoption. A critical success factor is the ability to stay ahead of industry trends, quickly validate new technologies, and operationalize high‑value capabilities in a regulated life sciences environment. Key Responsibilities 1. AI Platform Strategy & Architecture Help define and mature Exelixis' enterprise AI platform architecture across cloud and data ecosystems. Design interoperable solutions spanning: AWS AI stack (Bedrock, SageMaker, model hosting, orchestration) Databricks / Mosaic AI (ML lifecycle, feature engineering, LLM ops) Claude for Enterprise (secure conversational AI and enterprise workflows) Establish patterns for multi‑model orchestration, RAG architectures, and agent frameworks. 2. AI Capability Engineering & Operations Operationalize reusable AI capabilities: Model access layers (LLMs, fine‑tuned models) Prompt, tool, and agent orchestration frameworks Evaluation, monitoring, and observability pipelines Enable secure, compliant AI usage (GxP, HIPAA where applicable). Implement AI platform guardrails: Data access controls Responsible AI policies Auditability and traceability 3. Agentic & AI‑Native Engineering (Next‑Gen SDLC) Drive adoption of agentic software development lifecycle (SDLC) practices. Define frameworks for: Spec‑driven agentic development (Claude Code, GitHub Copilot, code agents) Autonomous/semiautonomous agents across workflows Integrate AI‑native platforms into enterprise engineering workflows (CI/CD, DevSecOps). 4. Innovation & Technology Scouting Continuously scan AI/ML ecosystem trends (foundation models, agent frameworks, enterprise AI tooling). Rapidly prototype and validate emerging capabilities (e.g., new Bedrock models, Mosaic AI features, agent frameworks). Create POCs, pilots, and enterprise rollout pathways. 5. Cross‑Functional Enablement Partner with cloud engineering, data engineering, platform teams for integration patterns. Partner with security, compliance, and governance stakeholders. Develop architectural guidance and design standards for engineering teams. Enable internal adoption through reference architectures, playbooks, and reusable assets. Required Qualifications 7+ years in enterprise architecture, data platforms, or AI/ML engineering. 5+ years hands‑on experience with cloud AI platforms (AWS preferred). Proven experience with: AWS Bedrock and/or SageMaker Databricks (including Mosaic AI or MLflow ecosystem) Enterprise LLM platforms (e.g., Claude, OpenAI, or similar) Strong understanding of LLM architectures (RAG, fine‑tuning, embeddings, vector DBs, graph DBs, multi‑agent orchestration) Preferred Qualifications Experience in life sciences, pharma, or clinical trial ecosystems. Familiarity with: GxP validation processes for AI/ML systems Clinical/regulatory data workflows Experience designing secure, compliant systems in regulated environments (life sciences strongly preferred). Exposure to: Agent frameworks (LangChain, Semantic Kernel, etc.) AI observability and evaluation tooling Multi‑cloud / hybrid architectures Key Competencies Strategic + hands‑on balance (thinks like an architect, executes like an engineer). Ability to translate emerging AI trends into enterprise value. Strong systems thinking across platforms, data, and workflows. Excellent stakeholder communication, able to influence senior leadership and engineering teams alike. Bias for action—rapid experimentation and iterative delivery. Desired Skills and Experience All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance. #J-18808-Ljbffr