Hybrid GCP Cloud Engineer

at Ford Motor Company

• Job title: GCP Cloud Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: BigQuery, Cloud, Docker, Google Cloud Platform, OpenShift, Python, Terraform
• Location requirements: Hybrid, Chennai, India

About the role

• GCP Engineer specializing in Agentic AI technologies to design and maintain scalable AI platforms on Google Cloud. Working across the AI lifecycle from pipeline to infrastructure management.

Responsibilities

• Design and manage end-to-end AI agent build pipelines using Vertex AI Pipelines
• Automate data ingestion, feature engineering, training, evaluation, and deployment workflows
• Implement reproducible experiments and pipeline versioning
• Work with BigQuery for large-scale analytics and training datasets
• Manage datasets and artifacts in Google Cloud Storage
• Implement data lineage tracking for traceability and governance
• Implement Infrastructure as Code (IaC) using Cloud Build, Terraform, or similar tools for provisioning and managing GCP resources
• Build CI/CD pipelines for AI agent training and deployment
• Manage source control and collaboration using Git
• Containerize AI workloads using Docker
• Deploy batch and real-time Agent builds using Cloud Run Services, Cloud Run Jobs, or Openshift cluster/GKE (if applicable)
• Implement deployment strategies such as blue-green, canary, and rollback
• Build and deploy LLM-powered applications
• Implement Retrieval-Augmented Generation (RAG) pipelines
• Integrate and manage Vector Databases for embeddings and semantic search
• Implement AI agent/model lineage tracking and versioning
• Monitor AI agent/model performance, drift, and data quality in production
• Set up alerting and dashboards for AI agent/model health
• Design and manage secure, scalable, and cost-effective GCP infrastructure components
• Implement and enforce security best practices and IAM policies
• Proactively monitor and optimize GCP resource utilization and costs
• Troubleshoot and resolve infrastructure-related issues impacting AI workloads
• Develop production-grade AI agent services using Python or other relevant languages
• Package reusable AI components and libraries using PyPI or other appropriate methods
• Follow best practices for code quality, testing, and documentation

Requirements

• Bachelor's Degree or equivalent
• Strong experience with GCP services (Vertex AI, BigQuery, GCS, Cloud Run, GKE, Compute Engine, Cloud Networking)
• Solid understanding of AI algorithms and training workflows
• Hands-on experience with LLMs, RAG, and vector search systems
• Proficiency in Docker, Git, and CI/CD pipelines
• Strong Python programming skills
• Experience with infrastructure as code tools like Terraform or Cloud Deployment Manager
• Experience with data and AI agent/model lineage
• Knowledge of AI agent/model monitoring, drift detection, and observability
• Understanding of scalable AI agent deployment patterns
• Strong understanding of GCP security principles, IAM, and network security
• Experience with feature stores (Good to Have)
• Familiarity with MLflow or similar experiment tracking tools (Good to Have)
• Experience with cost optimization on cloud platforms (Good to Have)