Senior GenAI/ML Engineer

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

• Build working Gemini and ML services that move the organization from 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%

Requirements

• 5+ years of software, cloud, data, SRE, test, or ML engineering experience
• 2+ years of hands-on Google Cloud, AI/ML, data, or production-platform experience
• Experience with Python, Vertex AI, Gemini, ADK, RAG, ML, Cloud Run/GKE, APIs, testing, evaluation, and Git
• Active Secret clearance required
• TS/SCI eligibility preferred
• Google Cloud Professional Machine Learning Engineer or Professional Cloud Developer certification preferred
• Experience operating production AI services with CI/CD, monitoring, and rollback preferredWashington, DC / Northern Virginia area preferred

Core Competencies

Demonstrates expertise in building and deploying AI/ML services using Python and Google Cloud technologies, while ensuring secure practices and compliance with RMF/FedRAMP/DoD standards. Capable of mentoring team members and contributing to reusable standards in a collaborative environment.

Highest-signal resume keywords

• Python Development
• Google Cloud Experience
• Machine Learning Services
• Active Secret Clearance
• CI/CD Implementation

Hard Skills

• Software Engineering
• Cloud Engineering
• Data Engineering
• ML Engineering
• Model/RAG Logic Development
• Production Monitoring
• Testing and Evaluation
• APIs
• Git

Soft Skills

• Mentoring
• Collaboration

Certifications & Qualifications

• Google Cloud Professional Machine Learning Engineer
• Google Cloud Professional Cloud Developer

Industry Keywords

• RMF
• FedRAMP
• DoD Authorization
• Least-Privilege Practices

Tools & Technologies

• Vertex AI
• Gemini
• ADK
• Cloud Run
• GKE