AI Test Automation Lead - Must have AgenticAI & Healthcare experience

Overview

Remote
$60
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

Amazon Web Services
Artificial Intelligence
Automated Testing
Cloud Computing
Cloud Storage
Collaboration
Continuous Delivery
Continuous Integration
DICOM
Data Flow
Data Integrity
Data Science
Electronic Health Record (EHR)
Good Clinical Practice
Google Cloud Platform
Grafana
HIPAA
HL7
Health Care
JUnit
Machine Learning (ML)
Mentorship
Open Source
POSTMAN
QA Management
Quality Assurance
Real-time
Regression Analysis
Regulatory Compliance
Security QA
Selenium
Stackdriver
Storage
TensorFlow
Test Plans
Test Strategy
Testing
Vertex

Job Details

 

Agentic AI, Healthcare functional domain must

Leadership & Strategy

Lead end-to-end testing strategy and execution for AI/ML healthcare applications deployed on Google Cloud Platform.

Collaborate with product owners, solution architects, and data science teams to define quality benchmarks for AI-driven healthcare solutions.

Ensure compliance with healthcare regulations (HIPAA, HL7, FHIR, GDPR where applicable) in testing processes and data handling.

Test Planning & Execution

Design and implement test strategies for AI/ML models, APIs, data pipelines, and healthcare applications hosted on Google Cloud Platform.

Develop automated test frameworks using Google Cloud Platform-native tools (e.g., Cloud Build, Cloud Functions, BigQuery, Vertex AI) integrated with CI/CD pipelines.

Define validation approaches for AI models including accuracy, precision, recall, bias, fairness, and explainability.

Perform functional, integration, regression, performance, and security testing across healthcare platforms.

Data & Healthcare Domain Expertise

Validate data ingestion, transformation, and storage processes in Google Cloud Platform (Pub/Sub, Dataflow, BigQuery, Cloud Storage) ensuring healthcare data integrity and quality.

Test healthcare-specific standards such as HL7, FHIR APIs, DICOM imaging, and EHR/EMR integrations.

Ensure synthetic data usage and anonymization techniques are applied for protected health information (PHI).

Automation & Tools

Build reusable automation test suites for APIs, AI/ML pipelines, and cloud-based healthcare apps.

Leverage Google Cloud Platform tools (Vertex AI Pipelines, TensorFlow Extended (TFX)) and open-source frameworks (PyTest, Robot Framework, Selenium, Postman, JUnit) for AI validation.

Integrate testing with monitoring tools (Stackdriver, Prometheus, Grafana) for real-time healthcare application performance tracking.

Collaboration & Mentorship

Work with cross-functional teams including developers, data engineers, and clinicians to validate AI outcomes.

Mentor QA engineers on Google Cloud Platform, AI testing best practices, and healthcare compliance testing.

Act as a key liaison between business stakeholders and technical teams to ensure quality delivery of AI healthcare solutions.

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