Overview
Remote
$70 - $80
Contract - W2
Contract - 12 Month(s)
Skills
GCP platform
AI applications
LangGraph
Python
Gemini APIs
GCP tools
EHR
FHIR
HL7
Job Details
Google Cloud Platform AI Engineer/ Architect
Remote
Duration: 12+ Months
MUST HAVES:
Will be building AI applications on Google Cloud Platform platform.
Must have prior Google Cloud Platform + AI Engineering experience
Description:
- 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 Google Cloud Platform 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 Google Cloud Platform 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.
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