AI Platform Engineer (Strong Senior/Lead DevOps/MLOps)

We are seeking a hands-on AI Platform Engineer to join our team. The primary mission of this role is to operate, automate, manage, and evolve

our enterprise AI Platform so that internal development teams can rely on a stable, secure, scalable, and well-governed environment for building AI solutions.

This is a platform engineering and operations role, not an application development position. The ideal candidate is proactive, autonomous, understands cloud platform engineering principles, and can execute technical initiatives with minimal supervision.

The role spans infrastructure, CI/CD automation, API management, platform governance, and AI services, with a strong emphasis on Infrastructure as Code and operational excellence.

Requirements:

Hands-on experience operating enterprise platforms in Microsoft Azure environments

Strong experience with Terraform and Infrastructure as Code practices

Experience designing and maintaining CI/CD pipelines using Azure DevOps

Practical knowledge of Azure API Management (APIM)

Experience with Azure AI Foundry, Azure OpenAI, or related Azure AI services

Understanding of cloud networking, security, identity management, and access control

Strong troubleshooting and problem-solving skills.

Proven ability to work autonomously and manage tasks end-to-end

Nice-to-Have Skills:

Experience with Portkey AI for LLM routing, observability, guardrails, caching, or governance

Knowledge of multi-model AI platforms and model gateway architectures

Familiarity with AWS Bedrock or other cloud AI platforms

Experience implementing platform observability solutions and operational dashboards

Knowledge of enterprise AI governance, compliance, and security controls

Candidate Profile:

Operates independently while keeping stakeholders informed and aligned

Has a platform-first mindset and understands how developers consume shared services

Is comfortable working across infrastructure, DevOps, API management, and AI services

Takes ownership of operational excellence, automation, and continuous improvement

Is proactive, reliable, and capable of driving technical tasks from design through implementation

Learns quickly and adapts to an evolving cloud and AI technology landscape

Values documentation, standardization, and long-term maintainability of platform solutions

Job responsibilities:

AI Platform Operations

Troubleshoot platform-level issues and coordinate resolution across multiple Azure services

Support platform scalability, reliability, availability, and operational excellence

Manage lifecycle operations for LLMs, embedding models, AI services, and platform environments across development, non-production, and production

Administer and maintain Azure AI Foundry workspaces, projects, model deployments, connections, and platform configuration

Infrastructure as Code & Automation

Develop, maintain, and enhance Infrastructure as Code using Terraform

Build and manage reusable infrastructure modules, templates, and deployment patterns

Automate environment provisioning, configuration management, and platform operations

Ensure consistency and repeatability across environments through automation

CI/CD & DevOps

Design, implement, and maintain CI/CD pipelines using Azure DevOps

Manage build, release, deployment, validation, and rollback processes

Improve deployment reliability through testing, automation, and release governance

Promote DevOps best practices across the platform ecosystem

API Platform & Integration Management

Operate and maintain Azure API Management (APIM) as a core component of the AI Platform

Configure APIs, policies, authentication, authorization, throttling, and routing mechanisms

Support secure exposure of AI capabilities to internal development teams

Assist in troubleshooting API connectivity, authentication, and integration challenges

Observability & Monitoring

Configure and maintain platform-wide logging, monitoring, tracing, and telemetry

Build dashboards and reporting for platform usage, performance, adoption, cost, and operational health

Monitor platform capacity, quotas, consumption, and service reliability

Implement alerting and diagnostics to ensure stable platform operations