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# Azure Platform Engineer

- **Company:** CGI Group
- **Location:** Buffalo, NY, United States
- **Experience:** Expert
- **Salary:** $71,700.0 - $188,100.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, Microsoft Azure, Bash Shell, Continuous Integration, Github, Python (Programming Language), Windows PowerShell, Role-Based Access Control, Reliability Engineering, Prometheus, Azure Machine Learning, Search Technologies, Security Information and Event Management, Management of Software Versions, Data Logging, Large Language Models, Grafana, Multi-Agent Systems, Rate Limiting, Web Filtering, AI Platforms, Gitlab-ci, Information Technology, Low Latency, Machine Learning Operations, Terraform
- **Published:** September 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1d4ad6c4380eedb5

## About the Role

At least 5+ years of experience in as an Azure Platform Engineer, Site Reliability engineering, platform operations, or infrastructure engineering.
.Hands on experience with Azure infrastructure (APIM, Monitor, Log Analytics, Entra ID, Terraform). You can build and troubleshoot, not just architect.
.Experience building observability pipelines (OpenTelemetry, Prometheus, Grafana, or Azure native equivalents). You know the difference between metrics, traces, and logs and when each matter.
.Experience with CI/CD for infrastructure (Terraform, GitHub Actions or GitLab CI, IaC patterns).
.Strong scripting and automation skills (Python, Bash, PowerShell). You automate operational tasks by default.
. Available for on call production support systems.

Desired qualifications/non essential skills required
.Experience with LLM specific operational concerns: token cost tracking, model latency monitoring, provider failover, rate limiting per caller identity.
.Experience with SIEM integration and security event feeds from application infrastructure.
.Familiarity with AI gateway patterns (prompt logging, PII interception, content filtering at the infrastructure layer).
.Experience in a regulated environment where audit trails and change management are mandatory.

Education: Bachelor's degree in computer science or related field.

## Description

As an Azure Platform Engineer, you will help build, automate, monitor and operate production Azure environments, with a focus on reliability, security, observability and cost management. You will work with Azure infrastructure, APIs, CI/CD pipelines and Infrastructure-as-Code while supporting the operational needs of enterprise AI platforms.
We are looking for a hands-on platform engineer with strong operational ownership and automation skills; someone who can troubleshoot production issues, build repeatable infrastructure and help maintain a secure and reliable platform.

This is a Full-Time, on-site employment opportunity based in Buffalo, NY (Preferred) or any CGI office in East Coast in a Hybrid Model with travel to Buffalo as required., Design, build, and operate the Azure AI platform infrastructure (Azure OpenAI, Azure AI Foundry, Azure Machine Learning, AI Search, networking, and identity) that other teams build on top of.
.Implement platform level controls required by governance policy: content filtering, prompt/response logging, access controls, rate limiting, and data residency enforcement.
.Manage provisioning, scaling, and cost governance for AI workloads across resource groups, subscriptions, and environments (dev/test/prod).
.Build and maintain CI/CD pipelines for model deployment, prompt/config versioning, and infrastructure as code for AI services.
.Own platform security posture: private endpoints, managed identities, RBAC, key/secret management, and integration with enterprise security tooling.
.Monitor platform health, latency, and reliability (SLOs/SLIs) for AI services, and lead incident response for platform level outages or degradations.
.Partner with the AI Governance Lead to implement policy requirements as technical controls, and flag where policy asks exceed current platform capability.
.Support FDEs and application teams by maintaining reusable platform components (RAG scaffolding, agent orchestration patterns, connectors) so they aren't rebuilding infrastructure per engagement.
.Evaluate and onboard new Azure AI capabilities (new models, agent frameworks, evaluation tools) and assess their fit for the platform roadmap.
.Maintain documentation of platform architecture, configuration standards, and runbooks to support audits and onboarding., Azure
Infrastructure
Observability
Python
SRE (Site Reliability Engr.)
Terraform
Azure - Data & AI
Azure - Infrastructure
Azure Functions
Azure Redis Cache