AI DevOps Engineer

Ingersoll Rand is committed to achieving workforce diversity reflective of our communities. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  Role Summary Enable and scale Ingersoll Rand’s GenAI program by designing, building, and operating the production infrastructure that powers AI-driven applications across the enterprise. This role focuses on  DevOps, cloud infrastructure, CI/CD, observability, and platform reliability  for GenAI systems built on  LLM APIs and Snowflake-native capabilities . Own the operational lifecycle of LLM-powered systems including prompt versioning, model configuration, cost controls, and production reliability across Snowflake-native and API-based GenAI platforms. You will work closely with AI engineers and application developers to turn prototypes into  secure, reliable, observable, and scalable AI applications , ensuring smooth integration with enterprise systems and data platforms. This is a DevOps and platform engineering role with a strong focus on production-grade AI systems. The Core Challenge GenAI teams can build powerful applications quickly using LLM APIs—but productionizing them at enterprise scale is hard. Challenges include environment consistency, secure data access, observability, cost control, CI/CD automation, and reliable integrations with core business systems. This role bridges that gap by providing  standardized infrastructure, deployment pipelines, and operational frameworks  so AI teams can move fast without sacrificing reliability, security, or governance. Key Responsibilities GenAI Platform & Infrastructure Design, build, and maintain cloud infrastructure to host GenAI applications using  GCP and Snowflake container services Support Snowflake-based AI workflows including  data ingestion, Cortex Agents, Analyst, and Search Define standardized, reusable infrastructure patterns for AI applications across development, staging, and production environments Implement cost-aware infrastructure patterns (warehouse sizing, service isolation, token budgeting) for GenAI workloads Explore, build, and support proof-of-concept initiatives to evaluate emerging GenAI and MLOps platforms and architectures, focusing on deployment, orchestration, monitoring, and governance of LLM-based systems. CI/CD & Automation Build and maintain  CI/CD pipelines using GitHub  for AI applications and platform services Automate infrastructure provisioning and environment configuration using Infrastructure-as-Code Enable…