AI DevOps Engineer

Responsibilities

• Design, build, and maintain cloud infrastructure to host GenAI applications using GCP and Snowflake container services
• Build and maintain CI/CD pipelines using GitHub for AI applications and platform services
• Automate infrastructure provisioning and environment configuration using Infrastructure-as-Code
• Implement observability for GenAI systems using Langfuse and Snowflake observability tools to monitor health, latency, and cost
• Manage containerized workloads across GCP and Snowflake containers
• Support and operationalize integrations between GenAI applications and enterprise systems like SAP, Salesforce, and SharePoint
• Define standardized, reusable infrastructure patterns for AI applications across development, staging, and production environments

Requirements

• 3+ years in DevOps, platform engineering, or software infrastructure roles
• 1-2+ years specifically with ML/AI infrastructure or MLOps
• Experience operating LLM-based applications in production, including prompt management and cost monitoring
• Strong experience with CI/CD pipelines (GitHub Actions preferred)
• Hands-on experience with containerized applications (Docker, Kubernetes or managed platforms)
• Experience operating workloads on GCP or similar cloud platforms
• Proficiency with Infrastructure-as-Code tools such as Terraform
• Strong scripting skills in Python and/or Bash
• Experience implementing monitoring, logging, and observability for production systems
• Fluent in English (written and spoken)
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, IT, or a related field

Preferred Qualifications

• Experience with Snowflake, including data ingestion pipelines and Snowflake-native applications
• Familiarity with GenAI application architectures (RAG, agents, prompt orchestration)
• Experience with Langfuse or similar AI observability tools
• Knowledge of vector databases (Pinecone, Weaviate, Milvus, Chroma)
• Experience with data versioning tools (DVC, Pachyderm, LakeFS)
• Cloud or MLOps certifications (GCP ML Engineer, Kubernetes CKA/CKAD, etc.)

About the Company

Ingersoll Rand is a global provider of mission-critical flow creation and industrial solutions. Driven by an entrepreneurial spirit, we are dedicated to helping make life better for our employees, customers, and communities through technology-driven excellence.