GCP AI Engineer

Job Title: GCP AI Engineer
Location-Type: Remote
Start Date: 2 weeks after verbal offer
Duration: Contract, 6 months (potential to convert to permanent)

Compensation Range: $100-111/hr W2

Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship

Job Description:
This role is responsible for hands-on engineering of AI-powered solutions within a large, complex healthcare data environment, delivering working prototypes and production-ready applications that help the client validate and scale AI initiatives.

Job Summary
Build AI-powered solutions focused on clinical notes and document processing within a healthcare data environment.
Develop AI agents and RAG systems using Google Cloud's AI ecosystem, including Vertex AI, BigQuery, and Gemini.
Construct POCs and prototypes to validate AI use cases and demonstrate business value to the client.
Apply DevOps and MLOps practices to move AI solutions from development into production, including CI/CD pipelines and monitoring.
Navigate ambiguous, incomplete requirements by working with stakeholders to define scope and drive progress.
Communicate complex technical concepts clearly to non-technical stakeholders and leadership.
Understand data lineage and how data flows through complex healthcare environments, including clinical and financial data.

Minimum Requirements:
6 years of experience in a hands-on AI or data engineering role, ideally with a consulting background.
Demonstrated GCP experience with Vertex AI, BigQuery, and Gemini, including production deployments.
Experience building and shipping GenAI solutions, including RAG pipelines and AI agents, in a corporate environment.
Strong Python skills and software engineering fundamentals.
Hands-on experience with DevOps and MLOps practices, including CI/CD and model monitoring.
Experience working with healthcare or similarly regulated data environments, including clinical notes, EHR data, or HIPAA/PII data.
Preferred Qualifications:
Experience with clinical note and unstructured document processing in a healthcare or health finance context.
Familiarity with healthcare data standards such as HL7 or FHIR.
Background working in a consulting or professional services environment with multiple clients or data environments.
Experience communicating AI feasibility and ROI to non-technical stakeholders or leadership.