We are seeking a highly skilled and experienced Senior DevOps Engineer with expertise in AI to manage foundational infrastructure for Generative AI applications, with a focus on GCP, GKE, Vertex AI, and Python-based frameworks.
Work with a major company that aggregates broad and deep property data and generates analytics that inform smart decision-making and property-level insights that hundreds of thousands of users in the real estate industry rely on.

REQUIREMENTS

• 3+ years of experience in DevOps, cloud infrastructure, or AI platform operations, specifically with GCP
• Expertise in deploying and managing Google Kubernetes Engine (GKE) and Vertex AI solutions for production environments
• Proficiency in Python and experience orchestrating AI tools/frameworks like LiteLLM, Dify.AI, CrewAI, and Guardrails AI
• Proven experience with cloud-native deployments and modern container orchestration tools
• Proficiency with GenAI or Agentic AI concepts, tools, and applications
• Working knowledge of AI governance and security best practices
• Competency in containerization technologies such as Docker and Kubernetes
• Strong knowledge of cloud platforms (GCP), particularly with services like Vertex AI, GKE, and BigQuery
• Familiarity with monitoring and logging systems such as Prometheus, Grafana, or Stackdriver
• B2 level of English or higher, with an emphasis on technical communication skills

• Design, deploy, and manage scalable, secure, and optimized cloud infrastructure on GCP, including GKE clusters and Vertex AI workflows, to support GenAI applications
• Integrate and support Python-based AI tools and frameworks like LiteLLM, Dify.AI, CrewAI, and Guardrails AI to ensure seamless operation within the Agentic AI platform
• Build and maintain automated CI/CD pipelines and implement infrastructure provisioning to improve platform scalability and efficiency
• Implement monitoring, logging, and alerting solutions to ensure the performance, reliability, and availability of AI services, while resolving operational issues effectively
• Ensure adherence to security best practices, governance standards, and data protection measures to maintain a secure and compliant AI infrastructure