Google Cloud Platform AI Engineer Health Tech (Agentic AI & Next-Gen AI Tech)

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Must have prior GCP + AI Engineering experience.

Job Details

Google Cloud Platform AI Engineer Health Tech (Agentic AI & Next-Gen AI Tech)

Location: 100% remote in the US

Duration: Long term

MUST HAVES:

  • Must have prior Google Cloud Platform + AI Engineering experience.

Overview
As a Google Cloud Platform 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 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.

  • Security & Compliance: Apply best practices in privacy, IAM, VPC, and encryption for health data. Enforce regulatory compliance (HIPAA, GDPR) within all engineering work.
  • Collaboration & Support: Work closely with clinical, product, and IT teams; provide hands-on technical support and documentation for operationalized systems in healthcare environments.

  • Continuous Learning & Prototyping: Stay current with new Google Cloud Platform, agentic, and GenAI advances; contribute to prototypes, validation methods (including Turing Test compliance), and deployment of secure agent workflows.

Required Qualifications

  • Bachelor s or Master s in Computer Science, Engineering, Health Informatics, AI, or similar.
  • 4+ years of hands-on engineering experience developing and deploying AI/ML solutions on Google Cloud Platform, with direct experience in clinical/healthcare environments.
  • Demonstrated expertise with MLOps and AI Ops (Vertex AI, Kubeflow, MLflow, CI/CD, monitoring, and workflow orchestration tools).
  • Proven programming skills in Python, plus experience with Docker, Kubernetes, cloud automation, and Terraform.
  • Direct experience creating agentic AI applications, troubleshooting APIs (Gemini, agent development kits), and deploying healthcare agents and RAG applications.
  • Familiarity with clinical data standards (FHIR, HL7), EMR systems (EPIC), and best practices for data security and governance in health tech.
  • Google Cloud Professional certifications (AI Engineer, DevOps, Cloud Architect, Data Engineer) highly desirable.

Desired Competencies

  • Experience with operationalizing GenAI for healthcare (conversational agents, clinical summarization, documentation automation).
  • Skill in data processing, workflow orchestration (Cloud Composer), and error troubleshooting for healthcare pipelines.
  • Proven ability integrating trust frameworks, AI validation, and compliance methods into healthcare and agentic applications.
  • Strong stakeholder communication, technical support, and documentation abilities.

Kiran Kumar

Key Business Solutions, Inc.

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