Principal AI Engineer/Architect.

About This Opportunity

CTI Staffing is partnering with a leading healthcare and enterprise technology consulting organization to find a Principal AI Engineer/Architect for their AI delivery team, based in Nashville, TN (remote considered).

This team builds production-grade AI applications that connect clinical and enterprise data, tools, and workflows for regulated healthcare and enterprise clients. They're moving past AI prototypes into governed, scalable systems that clinicians and operations teams actually use every day.

What You'll Do

• Design and build agentic AI systems that reason across tasks, use tools, and orchestrate multi-step workflows with human-in-the-loop review
• Develop AI solutions on Google Cloud, including Vertex AI, Gemini models, Agent Builder, Vertex AI Search, Document AI, and BigQuery
• Build LLM-powered pipelines that extract, summarize, and structure clinical and healthcare documents
• Establish CI/CD and MLOps pipelines, infrastructure-as-code, and observability practices for AI applications
• Build retrieval-augmented generation solutions connecting securely to clinical content and enterprise data
• Implement authentication, authorization, and governance controls so AI systems handle sensitive data safely and compliantly
• Define evaluation approaches for agent performance, retrieval relevance, and hallucination risk
• Serve as a hands-on technical advisor embedded with client teams, resolving implementation blockers and mentoring engineers

Requirements

What You Bring

Must-Have:

• 6+ years in software engineering, cloud engineering, AI engineering, or solution architecture, ideally in consulting or client-facing delivery
• Hands-on experience designing agentic AI applications — orchestration, tools, memory, planning, multi-step workflows, RAG
• Strong experience with Vertex AI and the broader Google Cloud AI ecosystem
• Strong proficiency in Python, TypeScript, or Go, and frameworks like FastAPI, LangChain, or LangGraph
• Experience with GitHub Actions, Cloud Build, CI/CD, Terraform, and containers (GKE and Cloud Run)
• Experience integrating AI with clinical/operational systems and healthcare data standards such as HL7 and FHIR
• Experience handling PHI in regulated environments
• Understanding of AI evaluation, monitoring, tracing, and model behavior analysis

Nice-to-Have:

• Google Cloud Professional Machine Learning Engineer, Professional Cloud Architect, or Generative AI Leader certification
• Kubernetes (CKA) or Terraform certification
• HIPAA or Responsible AI governance certification
• Prior forward-deployed or embedded consulting engineering experience
• Experience mentoring engineers or building reusable delivery accelerators

Technical Environment:

• Google Cloud Platform, Vertex AI, Gemini, Agent Builder, Vertex AI Search, Document AI, BigQuery
• Python, TypeScript, Go, FastAPI, LangChain/LangGraph
• Terraform, GKE, Cloud Run, GitHub Actions, Cloud Build

What Success Looks Like:

• A production agentic AI system live and observable within a client workflow inside the first few months
• Governance and security controls in place that pass a real compliance review
• Reusable architecture patterns documented for future engagements