Senior ML engineer

Grid Dynamics is a company hiring for a strategic engineering squad to build next-generation intelligent agent infrastructure for the world’s largest home improvement retailer, focusing on enterprise-grade AI applications and autonomous agents.

• 5+ years hands-on experience in Cloud & AI software engineering with focus on production AI/ML systems on Google Cloud Platform (GCP).
• Experience building and deploying intelligent agents with Vertex AI, Agent Engine, and Google Cloud Agent Development Kit (ADK).
• Strong proficiency in Python for AI development and data processing.
• Hands-on experience with Model Context Protocol (MCP) design and implementation.
• Experience with Infrastructure as Code using Terraform and CI/CD pipelines with GitHub Actions.
• Practical understanding of enterprise cloud security including Workload Identity Federation, RBAC, Open Policy Agent (OPA), VPC, and private endpoints.
• Experience with AI observability and monitoring tools such as OpenTelemetry, Grafana, and LangSmith.
• Experience with messaging frameworks and NoSQL data stores (Google Pub/Sub, Elasticsearch, BigTable).
• Excellent problem-solving skills and English communication.

Nice to have:

• Practical experience with containerization and orchestration tools: Docker, Kubernetes, Google Kubernetes Engine (GKE).
• Experience with cross-cloud identity federation (Azure AD to Google Workspace).
• Familiarity with real-time alerting systems (PagerDuty) and automated policy enforcement frameworks.
• Experience in retail, supply chain, or high-throughput e-commerce platforms.

• Design, implement, and maintain secure, scalable AI agent infrastructure on Google Cloud Platform using Vertex AI, Agentspace, and the Agent Development Kit (ADK).
• Build, deploy, and manage custom Model Context Protocol (MCP) actions.
• Establish enterprise security and Identity Access Management frameworks including Workload Identity Federation, short-lived tokens, RBAC, and cross-cloud alignment.
• Design automated CI/CD pipelines and Infrastructure as Code (IaC) using Terraform and GitHub Actions.
• Develop event-driven workflow orchestrations and scalable data pipelines using Google Pub/Sub, Python, Elasticsearch, and BigTable.
• Implement continuous monitoring and observability using OpenTelemetry, Grafana, LangSmith, and automated alerting.
• Enforce policy-as-code and real-time security using Open Policy Agent (OPA), VPC, and private endpoints across Google Kubernetes Engine (GKE) and containerized environments.

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