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AI Architect

METANLYTICS LLCNashville, TN🇺🇸United StatesPosted 19 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Ai Architect

 

What We''re Looking For
Experience: 6+ years of experience in software engineering, cloud engineering, AI engineering, enterprise application development, or solution architecture, ideally in consulting, healthcare, or client-facing delivery environments.
Agentic Systems Expertise: Hands-on experience designing and building agentic AI applications, including orchestration, tools, memory, planning, multi-step workflows, RAG, and human-in-the-loop controls.
Google Cloud AI Platform Depth: Strong experience with Vertex AI and the broader Google Cloud AI ecosystem, including Gemini models, Vertex AI Agent Builder, Vertex AI Search, Document AI, BigQuery, or related Google Cloud services.
Software Engineering Foundation: Strong proficiency in modern programming languages and frameworks commonly used for AI application development, such as Python, TypeScript, Go, FastAPI, LangChain/LangGraph, or similar technologies.
DevOps and Cloud Engineering: Experience with GitHub Actions, Cloud Build, CI/CD, infrastructure-as-code (Terraform), containers (GKE and Cloud Run), APIs, monitoring, logging, environment promotion, and production release management.
Clinical Operations & Healthcare Data: Experience integrating AI with clinical and operational systems—EHRs, clinical documentation, and healthcare data standards such as HL7 and FHIR—including handling of PHI in regulated environments.
AI Quality and Observability: Understanding of AI evaluation, prompt/version management, automated testing, telemetry, tracing, monitoring, model behavior analysis, and operational support patterns.
Consulting Mindset: Strong communication skills with the ability to translate technical tradeoffs into practical recommendations for executives, clinical leaders, platform teams, security stakeholders, and operations users.

Preferred Certifications
Google Cloud / AI: Google Cloud Professional Machine Learning Engineer, Professional Cloud Architect, Generative AI Leader, or relevant Google Cloud and AI certifications.
DevOps / Engineering: GitHub, Google Cloud Professional DevOps Engineer, Kubernetes (CKA), Terraform, or cloud-native engineering certifications.
Healthcare / Governance: HIPAA, Responsible AI, or healthcare data and AI governance-related certifications are a plus.

Physical Requirements:
Ability to sit for extended periods while working at a computer
Capable of using a keyboard, mouse, and other standard computer peripherals
Able to see and read computer monitors and documentation
Capable of hearing for virtual meetings and conference calls
Able to communicate verbally and in writing+

Skills

FastAPI
Machine Learning
BigQuery
Generative AI
GitHub Actions
Google Cloud
HIPAA
Kubernetes
Python
Terraform
TypeScript

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