AI Platform Engineer with DevOps

Role: AI Platform Engineer with DevOps Experience - DevOps, Docker (Software), GitHub, GitHub Actions, Information Technology (IT) Infrastructure, Kubernetes, Programming Languages, Red Hat Ansible,Software Product Design, Software Product Technical Knowledge, Software GenAI, LLM

What will you do?

• Develop value-add services which integrate with the existing DevOps stack
• Develop CICD pipelines using GitHub Actions, TypeScript, Python, Groovy and Jenkins
• Coach application teams on how to leverage DevOps offerings
• Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind
• Participate in new tool adoption, POC process and provide recommendations
• Evolve DevOps services beyond current state for application teams

What do you need to succeed?

Must-have:

• An engineer mindset, SDLC experience with production class delivery, strong analytical mindset, communication skills, and sense of ownership / drive
• Experience with application and system design patterns
• Experience with Docker or Kubernetes
• Experience with Agile methodologies, ie SCRUM
• Design, build, and operate enterprise AI/GenAI platforms supporting Large Language Models (LLMs) and AI-powered applications.
• Develop scalable LLMOps and MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.

Build reusable AI services including:

• Retrieval Augmented Generation (RAG) architectures
• Embedding and Vector Search Services
• AI Gateway and Inference APIs
• Agentic AI Orchestration Frameworks

Nice-to-have:

• Experience with Elastic Search and Kibana
• Experience using DevOps CICD tools such as GitHub, GitHub Actions, Jenkins, UrbanCodeDeploy
• Experience with a public cloud technology, i.e. Azure, AWS
• Experience building or supporting distributed applications