GCP AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP AI Engineer, remote for 6-12+ months, paying "competitive rate." Requires strong healthcare experience, prior GCP and AI engineering skills, and expertise in data engineering, MLOps, and AI model deployment. Only USC/GC candidates.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
560
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🗓️ - Date discovered
September 4, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
-
🧠 - Skills detailed
#FHIR (Fast Healthcare Interoperability Resources) #Data Processing #Cloud #ML (Machine Learning) #AI (Artificial Intelligence) #Langchain #GCP (Google Cloud Platform) #Looker #Monitoring #BigQuery #Dataflow #Python #Talend #Data Engineering #Data Pipeline #Automation #Terraform #Deployment
Role description
Role: GCP AI Engineer
Job Location: Remote
Duration: 6-12+ Months
Visa Type:- Only USC/GC
Active Linkedin 2021
String comm. Skills
Must be Healthcare/clinical Strong
MUST HAVES:
· Will be building AI applications on GCP platform. Team is building a "Primary Care Physician AI Assistant" -
· Must have prior GCP + AI Engineering experience.
Overview
As a GCP AI Engineer in our health tech team, you’ll lead the design, development, and deployment of AI solutions on Google Cloud that elevate patient care and streamline
healthcare operations. Your work will span data engineering, model building, and AI Ops— delivering intelligent, production-ready healthcare applications and agents.
You will actively build, deploy, monitor, and troubleshoot AI models and agents in healthcare settings, shaping the future of clinical and patient-focused innovations through real-world engineering and operational excellence.
Key Responsibilities
· Hands-On Agent Development: Build, troubleshoot, and optimize agentic AI applications—using frameworks such as LangChain and LangGraph, Python, and Gemini APIs on Google Cloud, directly embedding agents into clinical workflows and patient-facing apps.
· AI Ops (MLOps) Implementation: Design and automate MLOps pipelines for model lifecycle management (training, validation, deployment, monitoring, and updates) utilizing GCP tools (Vertex AI Pipeline, Kubeflow, Cloud Build, Terraform). Ensure reproducibility, traceability, and reliability in live environments.
· Data Engineering for Healthcare: Construct secure, compliant data pipelines integrating multiple health data formats (EHR, FHIR, HL7), focusing on clinical data processing, validation engines, and interoperability with EMR systems like EPIC.
· Develop & Deploy AI/ML Models: Build, test, and deploy robust AI models—focused on health tech applications like clinical decision support, patient interaction, and workflow automation, using Vertex AI, BigQuery, Dataflow, and Looker.
· Operational Reliability: Use GCP’s Cloud Operations Suite (Stackdriver) and custom health-tech metrics for continuous monitoring, error troubleshooting, and
distributed system reliability. Rapidly diagnose and resolve production issues.
Thanks & Regards,
Alok Kumar | TALENDICA
Sr. Technical Recruiter
44 Saratoga Lane, Monroe Township, NJ 08831
Role: GCP AI Engineer
Job Location: Remote
Duration: 6-12+ Months
Visa Type:- Only USC/GC
Active Linkedin 2021
String comm. Skills
Must be Healthcare/clinical Strong
MUST HAVES:
· Will be building AI applications on GCP platform. Team is building a "Primary Care Physician AI Assistant" -
· Must have prior GCP + AI Engineering experience.
Overview
As a GCP AI Engineer in our health tech team, you’ll lead the design, development, and deployment of AI solutions on Google Cloud that elevate patient care and streamline
healthcare operations. Your work will span data engineering, model building, and AI Ops— delivering intelligent, production-ready healthcare applications and agents.
You will actively build, deploy, monitor, and troubleshoot AI models and agents in healthcare settings, shaping the future of clinical and patient-focused innovations through real-world engineering and operational excellence.
Key Responsibilities
· Hands-On Agent Development: Build, troubleshoot, and optimize agentic AI applications—using frameworks such as LangChain and LangGraph, Python, and Gemini APIs on Google Cloud, directly embedding agents into clinical workflows and patient-facing apps.
· AI Ops (MLOps) Implementation: Design and automate MLOps pipelines for model lifecycle management (training, validation, deployment, monitoring, and updates) utilizing GCP tools (Vertex AI Pipeline, Kubeflow, Cloud Build, Terraform). Ensure reproducibility, traceability, and reliability in live environments.
· Data Engineering for Healthcare: Construct secure, compliant data pipelines integrating multiple health data formats (EHR, FHIR, HL7), focusing on clinical data processing, validation engines, and interoperability with EMR systems like EPIC.
· Develop & Deploy AI/ML Models: Build, test, and deploy robust AI models—focused on health tech applications like clinical decision support, patient interaction, and workflow automation, using Vertex AI, BigQuery, Dataflow, and Looker.
· Operational Reliability: Use GCP’s Cloud Operations Suite (Stackdriver) and custom health-tech metrics for continuous monitoring, error troubleshooting, and
distributed system reliability. Rapidly diagnose and resolve production issues.
Thanks & Regards,
Alok Kumar | TALENDICA
Sr. Technical Recruiter
44 Saratoga Lane, Monroe Township, NJ 08831
