AI Platform Engineer (AI+DevOps)

CanadaOnsiteContractPosted 2 months ago

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Role summary

The AI Platform Engineer (AI+DevOps) will join the AI Enablement team to build, maintain, and scale enterprise AI infrastructure, including agent orchestration platforms (NOVA), AI gateway services (LiteLLM), and RAG pipelines across multi-cloud environments (GCP, Azure). Responsibilities include developing and operating AI platforms, optimizing LLM routing and cost, implementing monitoring (Prometheus, Grafana), designing RAG pipelines, deploying services on Kubernetes (AKS, GKE), and automating infrastructure with tools like Terraform and Helm. The role requires strong Kubernetes, CI/CD, and cloud experience, proficiency in Python/TypeScript, and 5+ years of platform engineering/DevOps experience with at least 2 years in AI/ML platforms.

Here is the JD -

The AI Platform Engineer (AI with DevOps) 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:

5+ 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

Preferred Qualifications:

Experience with LangChain, LlamaIndex, or agent frameworks
Familiarity with LiteLLM, MCP, Backstage
Cost optimization for LLM workloads
Enterprise-scale AI platform experience

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

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