AI Architect – Generative & Agentic AI

🔥 14 hours ago

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Cencora

WebsiteLinkedInAll Job Openings

10,000+ employees

💼 Consulting

📦 Logistics

🏥 Healthcare

Consulting • Logistics • Healthcare

Cencora is a company dedicated to improving the health and well-being of both people and animals globally. Built on the legacy of AmerisourceBergen, Cencora offers a wide range of industry-leading solutions that encompass specialty logistics, warehousing, drug research, clinical development support, and more. They provide commercialization and patient access support and offer wholesale and specialty distribution services. Cencora serves a diverse clientele, including pharmaceutical companies, physician practices, pharmacies, and health systems. The company also extends its services to animal health, managing operations and delivering products for animal pharmaceutical care. With a strong global footprint, Cencora aims to reshape healthcare delivery through innovative products and solutions, striving to create healthier futures for all.

📋 Description

• Own end-to-end architecture for enterprise Generative AI and Agentic AI solutions from concept through production • Lead rapid proof-of-concept and MVP development to validate AI use cases and de-risk technical approaches • Architect scalable AI platforms using LLMs, RAG pipelines, vector databases, and multi-agent orchestration frameworks • Design API-first REST/GraphQL architectures exposing AI capabilities to downstream applications and enterprise systems • Define technology selection, architecture standards, and best practices for prompt engineering, model evaluation, AI governance, and Responsible AI • Architect and guide MLOps/LLMOps practices for deployment, monitoring, and model/agent lifecycle management • Lead architecture reviews and present designs to executive sponsors and engineering teams • Drive stakeholder alignment • Mentor AI engineers, set coding and architecture standards, and raise the technical bar across the team • Evaluate and select cloud-native AI services while balancing scalability, cost, security, and performance

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field • 6+ years of overall IT experience spanning software engineering, cloud architecture, and/or AI/ML • 3+ years of hands-on architecture experience specifically in Generative AI / Agentic AI systems • Strong expertise in Python and modern AI development frameworks • Demonstrated experience architecting solutions with LLMs (OpenAI, Claude, Gemini, Llama, or open-weight models) • Deep understanding of RAG architectures, vector databases (Pinecone, FAISS, Databricks Vector Databases, pgvector), and embedding models • Experience architecting on at least one major cloud platform (Azure, AWS, or GCP), including native AI services • Proven experience with MLOps/LLMOps: CI/CD, containerization (Docker/Kubernetes), observability, and evaluation frameworks • Strong grounding in AI governance, security, compliance, and Responsible AI practices • Excellent communication skills, with the ability to present architecture to both executives and engineers • Healthcare knowledge is strongly preferred; experience with healthcare distribution, specialty pharma data, or healthcare EMR/EHR systems (HL7, FHIR, claims, NDC-level data) is a significant advantage

🏖️ Benefits

• Medical, dental, and vision care • Backup dependent care • Adoption assistance • Infertility coverage • Family building support • Behavioral health solutions • Paid parental leave • Paid caregiver leave • Training programs • Professional development resources • Mentorship programs • Employee resource groups • Volunteer activities