Azure Platform Engineer-APIM & AI

Job Title: Platform Engineer AI Gateway & Integrations Experience: 4+ Years (Minimum 1 year relevant experience) Location: Hybrid (Remote)
Qualification: Bachelors Degree in Computer Engineering or equivalent
We are seeking an experienced Platform Engineer to join our enterprise AI gateway on Azure API Management (APIM). This platform sits at the center of how the organization safely and reliably connects applications to large language models and AI services, handling routing, security enforcement, and integration for AI backends including Azure OpenAI, Azure AI Foundry, Databricks, and Cohere. You will play a hands-on role in onboarding new AI use cases, hardening platform security, and evolving the gateway's architecture as adoption grows.

About Cloudaeon:

Cloudaeon is a global technology consulting and services company. We support companies in managing cloud infrastructure and solutions with the help of big data, DevOps and analytics.

We offer first-class solutions and services that use big data and always exceed customer expectations. Our deep vertical knowledge, combined with expertise in several enterpriseclass big data platforms, helps develop targeted solutions to meet our customers' business needs.

Our global team consists of experienced professionals with experience in various tech stacks. Every member of our team is very active and committed to helping our customers achieve their goals.

Key Responsibilities

• Own the technical onboarding of new AI use cases onto the gateway platform backend integration, authentication, routing, and quota/rate-limit configuration.
• Design, write, and maintain Azure APIM policies and reusable policy fragments for security controls, including PII detection and redaction, prompt-injection defense, content safety, and protected-material detection.
• Build and maintain backend pool architectures for model failover and load balancing across multiple AI providers and deployment tiers.
• Develop and maintain Infrastructure-as-Code (Bicep, Azure DevOps pipelines) so platform changes are version-controlled, testable, and repeatable.
• Troubleshoot integration issues across authentication flows, API routing, and network connectivity, including private endpoint and secure networking configurations.
• Produce clear onboarding documentation, templates, and runbooks that help other engineering teams self-serve onto the platform.
• Participate in security hardening work driven by penetration-test findings and evolving threat patterns, iterating on the platform's defenses over time.
• Contribute to observability improvements, ensuring the platform's health and usage are visible and actionable

Required Skills

• Hands-on experience with Azure API Management (APIM), including policy authoring, products/subscriptions, and named values.
• Solid working knowledge of core Azure platform services: Entra ID (app registrations, roles, RBAC), Azure networking (VNETs, private endpoints), and Azure App Gateway.
• Experience with Infrastructure-as-Code (Terraform preferred, Bicepor ARM templates also considered) and CI/CD pipelines (Azure DevOps or similar).
• Comfort working with REST APIs, authentication protocols (OAuth2, client credentials, token exchange flows), and JSON/JWT handling.
• Experience integrating with AI/ML platforms such as Databricks Model Serving, Azure AI Foundry, or similar.
• Exposure to LLM-specific concerns: prompt injection, semantic caching, token quota management, or AI guardrail systems.
• Exposure in any of the programming knowledge preferably Python
• Basic Azure networking knowledge
• Experience responding to and remediating penetration-test or security-audit findings.
• Familiarity with emerging AI-agent integration patterns (e.g., MCP, A2A) or similar service-to-service communication frameworks.
• Strong debugging and problem-solving skills, with experience in a policy-expression or general-purpose programming/scripting language.
• Clear written communication skills able to document technical processes for a non-specialist audience.
• A security-conscious mindset and genuine interest in building resilient, production-grade platforms.

Good to Have
Experience integrating with AI/ML platforms such as Databricks Model Serving, Azure AI Foundry, or similar.
Exposure to LLM-specific concerns: prompt injection, semantic caching, token quota management, or AI guardrail systems.
¢ Experience responding to and remediating penetration-test or security-audit findings.
¢ Familiarity with emerging AI-agent integration patterns (e.g., MCP, A2A) or similar service-to-service communication frameworks