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# AI Cloud Engineer

- **Company:** Apex Systems LLC
- **Location:** Dearborn, MI, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, BigQuery, Cloud Computing, Cloud Database, Computer Programming, Databases, Continuous Integration, Software Debugging, Disaster Recovery, Fault Tolerance, Identity and Access Management, Python (Programming Language), Machine Learning, MongoDB, Reliability Engineering, Scikit Learn, Kubernetes, Terraform, Programming Languages
- **Published:** June 27, 2026
- **Apply:** https://jobs.mitalent.org/job-seeker/job-details/JobCode/391209993

## About the Role

Education: Bachelor's Degree

Experience: 6+ years in IT, with 4+ years in development and 5+ years in database engineering with a focus on GCP and AI enablement.

Technical Skills: Practical experience in two coding languages or advanced expertise in one. Experience with Gemini Enterprise (or similar) and an understanding of MCP or equivalent patterns. Hands-on experience with GCP databases (Cloud SQL, AlloyDB, Spanner, Firestore, Memorystore, MongoDB, BigQuery), Dataplex, and Knowledge Catalog. Knowledge of GCP IAM, encryption, and CI/CD practices.

Preferred Qualifications

 * Experience building Internal Developer Platforms (IDPs).
 * GCP Professional Cloud Database Engineer or Data Engineer certification.
 * Proficiency in Terraform and programming (Python or Java).
 * Experience with Kubernetes (GKE) and database operators.
 * Understanding of statistical analysis, data modeling, and ML libraries.

## Description

* Lead the adoption of Gemini Enterprise for tasks such as query generation, debugging, and schema optimization.
 * Define and implement patterns integrating Model Context Protocol (MCP) with databases for contextual AI interactions.
 * Identify and deploy AI-driven automation for capacity planning, anomaly detection, and self-tuning.
 * Partner with AI/ML teams to embed machine learning, statistical models, and GenAI into data platform strategies.
 * Establish enterprise standards for metadata, including tagging, classification, lineage, and discoverability.
 * Align with security frameworks, manage GCP IAM, service accounts, and encryption, and implement secure agent practices.
 * Apply Site Reliability Engineering (SRE) practices to ensure availability, fault tolerance, and disaster recovery.
 * Establish scalable, secure, self-service database architectures and roadmaps on GCP.
 * Build and maintain Terraform templates for automated provisioning and lifecycle management.
 * Advise engineering, data, and AI teams on best practices while fostering an AI-assisted, platform-first culture.


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