AI DevOps/Platform Engineers
Role summary
The AI DevOps/Platform Engineer will be responsible for building, maintaining, and scaling enterprise AI infrastructure, including agent orchestration platforms (NOVA), AI gateway services (LiteLLM), and RAG pipelines across multi-cloud environments (GCP, Azure). Key duties involve developing and operating AI platforms, optimizing LLM routing and cost, implementing monitoring and observability tools, designing RAG pipelines, deploying services on Kubernetes (AKS, GKE), and automating infrastructure using CI/CD pipelines and tools like Terraform and Helm. The role requires strong proficiency in Python/TypeScript and experience with cloud platforms, Kubernetes, and CI/CD practices.
AI DevOps/Platform Engineers
Location; Remote-(Canada)
Duration: 12+ Months
The AI DevOps/Platform Engineer will join the AI Enablement team, focusing on building, maintaining, and scaling enterprise AI infrastructure. This includes proprietary agent orchestration platforms (NOVA), AI gateway services, and Retrieval-Augmented Generation (RAG) pipelines across multi-cloud environments.
Key Responsibilities:
- Platform Development & Operations:
- Develop, deploy, and maintain the NOVA agentic AI platform
- Manage LiteLLM as the central AI gateway
- Optimize LLM routing, cost control, load balancing, and failover
- Implement monitoring and observability (Prometheus, Grafana, OpenTelemetry)
- RAG Pipeline Development:
- Design and optimize RAG pipelines
- Maintain document ingestion, chunking, embeddings, and vector stores
- Build RAG on GCP and Azure using managed AI services and vector databases
- Infrastructure & DevOps:
- Deploy AI services on Kubernetes (AKS, GKE)
- Implement CI/CD with Jenkins, Opsera, GitHub Actions
- Automate infrastructure (Terraform, Helm, GitOps)
- Ensure security and compliance
- Agentic AI & Automation:
- Develop automation tools and scripts
- Build MCP servers for tool integrations
- Enable multi-agent orchestration and autonomous workflows
- Create SDKs, APIs, and developer documentation
Required Qualifications:
- 8+ years platform engineering/DevOps experience
- 2+ years AI/ML or LLM platform experience
- Strong Kubernetes, CI/CD, and cloud experience (GCP or Azure)
- Proficiency in Python and/or TypeScript
Technical Environment:
- AI Platforms: LiteLLM, LangChain, LangGraph
- Cloud: GCP, Azure
- Containers: Kubernetes, Docker, Helm
- CI/CD: Jenkins, GitHub Actions, Opsera
- Observability: Prometheus, Grafana, OpenTelemetry, Dynatrace
- Languages: Python, TypeScript, Bash
