AI Platforms Engineer

Role overview

Platform and infrastructure responsibilities

• Build and operate cloud infrastructure for AI platforms and agents, including compute, GPU compute, networking, storage, containers, and platform services.
• Provision and manage runtime, hosting, and deployment environments for AI models, services, and agents.
• Implement, configure, administer, and operate enterprise AI platforms.
• Support Azure AI Services, Azure OpenAI, Azure AI Foundry, MCP gateways, agents, APIs, connectors, and integration services.
• Build and support agents that securely connect to approved enterprise data sources, tools, APIs, and systems.
• Enable AI developer and coding assistants across engineering teams.

Use cases and operations

• Identify, assess, prioritize, and onboard AI use cases with business teams, including assistants, workflow automation, and function-specific agents.
• Support productionisation through testing, release readiness, monitoring, documentation, and operational handover.
• Coordinate with Cloud and Data Platforms teams on secure, scalable, governed solutions; contribute platform evaluations, model and tool assessments, proofs of concept, and roadmap inputs.
• Monitor health, usage, performance, cost, access, and operational issues; troubleshoot infrastructure, platform, integration, and data-access problems.
• Maintain documentation, operating procedures, runbooks, and AI solution records; improve automation, reusable patterns, and platform capabilities.
• Ensure compliance with enterprise security, data governance, responsible AI, and operational standards.

Required qualifications and experience

• Bachelor’s degree in computer science, information technology, engineering, AI, data science, or a related discipline.
• 6–8 years of hands-on experience in cloud, data, AI, integration, automation, or enterprise platform roles.
• Practical Microsoft Azure and AI-related cloud services experience, including building or operating cloud infrastructure.
• Experience provisioning compute, networking, storage, containers, and platform services.
• Experience supporting APIs, integrations, connectors, and enterprise connectivity frameworks.
• Understanding of AI platforms, AI agents, prompt-based solutions, enterprise AI use cases, data access, identity, permissions, security controls, and governance.
• Strong analytical, troubleshooting, and problem-solving skills; able to work effectively with technical teams and business stakeholders.

Preferred skills

• Experience with Azure AI Services, Azure OpenAI, Azure AI Foundry, Copilot, or similar enterprise AI platforms.
• Experience with MCP gateways, AI agents, tool calling, workflow automation, or agentic platforms.
• Familiarity with Claude Code, OpenAI Codex, GitHub Copilot, or Cursor.
• Experience with GPU compute, containers or Kubernetes, networking, model hosting, AI productionisation, Infrastructure as Code, or CI/CD.
• Exposure to Snowflake, Power BI, Azure Data Factory, or enterprise data platforms.
• Understanding of responsible AI, AI governance, model evaluation, and AI risk controls; experience creating technical documentation and runbooks.

Preferred certifications

• Microsoft Azure AI Engineer, Azure infrastructure or administrator, or AI, data, cloud, integration, automation, or security-related certifications are preferred.
• Snowflake or data platform certification is an advantage.

Pay and contract

• Pay starts at AED 20,000 per month.
• Contract duration is 9 months.

Location and work arrangement

• UAE, on-site; work location is in person.
• The description also specifies Abu Dhabi as the required location.