Senior GenAI/ML Engineer for Secure Production AI (GCP)

Jobtailor; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks an experienced AI/ML Engineer to build Gemini and ML services, develop Python-based production pipelines, and deploy secure, compliant solutions on Google Cloud. You will mentor teammates and contribute to reusable standards while supporting RMF/FedRAMP/DoD authorization activities.

Expect to work with Vertex AI, Gemini, ADK, and RAG, implementing CI/CD, monitoring, and robust testing in production environments. Some travel to customer sites (10–25%) is required.

Qualifications

• 5+ years of software, cloud, data, SRE, test, or ML engineering experience.
• Active Secret clearance required; TS/SCI eligibility preferred.
• Experience with Python, Vertex AI, Gemini, ADK, RAG, ML, Cloud Run/GKE, APIs, testing, and Git.

Responsibilities

• Build working Gemini and ML services moving architecture to demonstrated capability.
• Develop Python services, model/RAG logic, experiments, tests, deployment packages, and production monitoring.
• Implement solutions using Python, Vertex AI, Gemini, ADK, RAG, and ML.
• Apply least-privilege and secure practices.
• Mentor team members and contribute reusable standards.
• Support RMF/FedRAMP/DoD authorization activities.
• Travel to customer sites approximately 10–25%.

Skills

Python Development

Google Cloud Experience

Machine Learning Services

Active Secret Clearance

CI/CD Implementation

Education

Google Cloud Professional Machine Learning Engineer

Google Cloud Professional Cloud Developer

Tools

Vertex AI

Gemini

ADK

Cloud Run

GKE

APIs

Git

Job description

Jobtailor seeks an experienced AI/ML Engineer to build Gemini and ML services, develop Python-based production pipelines, and deploy secure, compliant solutions on Google Cloud. You will mentor teammates and contribute to reusable standards while supporting RMF/FedRAMP/DoD authorization activities.

Expect to work with Vertex AI, Gemini, ADK, and RAG, implementing CI/CD, monitoring, and robust testing in production environments. Some travel to customer sites (10–25%) is required.