Haystack
← Back to Jobs
Remote
Other
HI

Azure AI Gateway & Platform Architect

HAN IT Staffing Inc.United States🇺🇸United StatesPosted 1 Sept 2026

Why This Role Stands Out

This remote Azure AI Gateway & Platform Architect role offers a fantastic opportunity to shape enterprise-scale AI platforms on Azure, driving innovation in a highly sought-after field. You'll thrive here if you possess deep expertise in Azure, AI platform engineering, and a passion for building secure, scalable solutions, enabling you to make a significant impact.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
1 week ago
MicroservicesService MeshAzureCapacity PlanningComplianceGrafanaKubernetesLLMOnboardingPrometheusRESTRegulatory ComplianceRisk ManagementRoot Cause AnalysisStakeholder ManagementTerraform

Job Description

Hi Associates,
I hope you are doing well.
We are actively working on an urgent requirement with one of our key clients and believe your background could be a strong fit. Please share your updated resume in word format (.doc/.docx), along with your contact number and your availability for a quick discussion.
This is a time-sensitive opportunity, and we are moving quickly with submissions. I would appreciate 
your prompt response so we can discuss the role in detail.
Looking forward to hearing from you soon.
 
Job Title: Azure AI Gateway & Platform Architect (AIOps Lead)
Location: Remote
Job Type: Long Term Project/Fulltime
 
Experience:
12+ Years (Cloud, Platform Engineering, AI Platform Architecture, AIOps)
 
Role Summary:
We are seeking an experienced Azure AI Gateway & Platform Architect (AIOps Lead) to establish and operationalize an enterprise-scale AI platform on Azure. The role will be responsible for designing and implementing AI governance frameworks, Azure AI Gateway architecture, secure AI service consumption, observability, reliability engineering, and AI-driven operations (AIOps).
The ideal candidate will have deep expertise in Azure Cloud, Azure OpenAI, API Management, AI platform engineering, monitoring, automation, and large-scale enterprise platform deployment. The individual will drive the creation of a secure, scalable, and governed AI consumption model while enabling business teams to build and deploy GenAI solutions efficiently.
Key Responsibilities:
Azure AI Platform Establishment
  • Design and establish an enterprise-grade Azure AI Platform.
  • Define architecture standards, landing zones, governance controls, and reference architectures for AI workloads.
  • Create reusable platform patterns for GenAI, RAG, Agentic AI, and AI-assisted automation solutions.
  • Enable secure onboarding of business units and development teams onto the AI platform.
  • Define enterprise AI operating model, platform lifecycle, and service management framework.
Azure AI Gateway Architecture
  • Design and implement Azure AI Gateway strategy leveraging Azure API Management.
  • Establish centralized routing, throttling, cost management, security, monitoring, and policy enforcement for AI services.
  • Build abstraction layers for Azure OpenAI, third-party LLMs, embedding models, vector databases, and AI services.
  • Implement AI service catalog and model management framework.
  • Enable multi-model orchestration and model governance.
AI Governance & Security
  • Define enterprise AI governance standards.
  • Implement responsible AI controls, security guardrails, auditability, and compliance requirements.
  • Establish identity management, RBAC, secrets management, and access controls.
  • Drive implementation of data protection, AI risk management, and regulatory compliance practices.
  • Partner with security teams to review AI workloads and platform architecture.
AIOps & Intelligent Operations
  • Establish enterprise AIOps framework using Azure Monitor, Log Analytics, Application Insights, and Open Telemetry.
  • Implement AI-driven anomaly detection, predictive analytics, root cause analysis, and automated remediation.
  • Design self-healing operational workflows and intelligent incident management processes.
  • Build operational dashboards, observability platforms, and reliability metrics.
  • Reduce MTTR, improve service availability, and automate operational response activities.
Platform Engineering & Automation
  • Develop Infrastructure-as-Code solutions using Terraform/Bicep.
  • Automate deployment, configuration, governance, and compliance validation.
  • Enable CI/CD integration for AI services and platform components.
  • Implement platform monitoring, health checks, capacity planning, and performance optimization.
Stakeholder Management
  • Work closely with Enterprise Architecture, Cloud Engineering, Security, Data, and AI Engineering teams.
  • Establish architecture review processes and platform governance councils.
  • Present roadmap, architecture, and operational metrics to leadership and customer stakeholders.
  • Mentor engineering teams on AI platform best practices.
Required Skills:
Azure Cloud
  • Azure Landing Zones
  • Azure Resource Manager
  • Azure Networking
  • Azure Kubernetes Services (AKS)
  • Azure Functions
  • Azure App Services
  • Azure Storage Services
  • Azure Identity & Access Management
AI & GenAI
  • Azure OpenAI Service
  • Agentic AI Architecture
  • AI Gateway Patterns
  • Prompt Engineering
  • RAG Architecture
  • Vector Databases
  • AI Model Governance
  • LLM Deployment & Operations
API & Integration
  • Azure API Management (APIM)
  • REST APIs
  • Event-Driven Architecture
  • Microservices
  • Service Mesh
  • Enterprise Integration Patterns
AIOps & Observability
  • Azure Monitor
  • Application Insights
  • Log Analytics
  • Open Telemetry
  • Prometheus / Grafana
  • Intelligent Alerting
  • Incident Automation
  • Root Cause Analysis
  • Self-Healing Automation
DevSecOps
  • Azure DevOps / GitHub
  • CI/CD Pipelines
  • Terraform / Bicep
  • Policy as Code
  • Security Automation
  • Infrastructure as Code
Preferred Qualifications:
  • Microsoft Certified: Azure Solutions Architect Expert
  • Microsoft Certified: Azure AI Engineer Associate
  • Azure DevOps Expert Certification
  • Experience implementing Azure OpenAI platforms for Banking or Financial Services clients.
  • Experience establishing enterprise AI Centers of Excellence (CoE).
  • Experience with GitLab Duo, GitHub Copilot, MCP, Agentic AI, and Enterprise AI Governance.

Similar jobs

Browse related jobs

Apply now