Company Overview

Open Innovation AI is a global technology company that specializes in developing advanced solutions for managing AI workloads. Its flagship product, the Open Innovation Cluster Manager (OICM), orchestrates complex AI tasks efficiently across diverse infrastructures. The platform is hardware-agnostic, optimized for various GPUs and accelerators hardware, and facilitates seamless integration and scalability for enterprise AI applications.

Open Innovation AI focuses on optimizing and simplifying AI workload management and making AI technologies accessible to organizations of all sizes. With its innovative solutions, companies can reduce operational costs, accelerate time to value, and maximize their return on investment, ensuring that their AI strategies contribute directly to enhanced business outcomes.

Role Overview:

The Service Desk Analyst is the first point of contact for customers using Open Innovation’s AI platform and the applications built on it. The role combines service desk discipline with working knowledge of the product: the analyst is expected to understand how the platform behaves, navigate the official product documentation confidently, and use it to answer customer questions and resolve issues whose cause and remedy are documented.

Support is delivered entirely remotely, with no access to customer clusters or environments. Resolution therefore depends on precise questioning and on guided screen-sharing sessions where the customer performs the steps and the analyst directs them. Where an issue falls outside documented behaviour, the analyst collects complete, structured diagnostic evidence and hands it to L2 Support so the receiving engineer can begin investigating immediately.

Role Responsibilities:

• Act as the first point of contact for customer requests arriving through Jira Service Management, email, phone, and monitoring alerts.
• Answer customer questions on platform functionality using the official product documentation.
• Resolve issues whose cause and remedy are described in the product documentation, runbooks, or knowledge base, and confirm the outcome with the customer before closing the ticket.
• Run guided screen-sharing sessions in which the customer demonstrates the issue and performs the steps, directing them clearly towards either a resolution or the evidence needed for escalation.
• Interpret what the customer shows or sends (error messages, job and pod status, container logs, dashboard panels, API responses) and determine whether the behaviour is expected, a configuration matter, or a product defect.
• Collect complete diagnostic evidence before escalating: environment, timestamps, job or request identifiers, exact error text, configuration used, reproduction steps, and what has already been ruled out.
• Escalate to L2 Support in a structured, self-contained form so the receiving engineer can start investigating without returning to the customer for basic detail.
• Retain ownership of the ticket after escalation: track progress, keep the customer informed at agreed intervals, and manage expectations on timelines through to closure.
• Monitor the Service Desk queues for acknowledgement and response SLA compliance, correct categorisation, and correct priority.
• Identify recurring questions and gaps in the documentation, and write knowledge base articles that let the next analyst resolve the same issue at first contact.
• Keep pace with release notes, new features, and changes in documented behaviour across the platform and its applications, so that product knowledge stays current release to release.
• Participate in structured shift handovers and operate in 24/7 rotational shifts, including nights, weekends, and public holidays as required

Required experience & Qualification

• Bachelor’s degree, preferably in Computer Science, Information Technology, Information Systems, or an equivalent field.
• 1 - 3 years in application support, product support, or technical service desk work supporting a software platform, rather than end-user desktop support.
• Demonstrated ability to read technical product documentation, apply it to a problem not seen before, and explain the answer to a customer in plain language.
• Conceptual understanding of Kubernetes: containers, pods, nodes, namespaces, deployments, and the meaning of common states such as Pending, CrashLoopBackOff, and OOMKilled.
• Comfortable on the Linux command line, and able to read application and container logs to locate the relevant error.
• Familiarity with REST APIs: interpreting HTTP status codes, request and response payloads, and token-based authentication, and reading YAML and JSON accurately.
• Basic networking literacy: DNS, TLS and certificates, proxies, and the typical symptoms of connectivity failures.
• Understanding of AI/ML workload fundamentals, including training, fine-tuning, inference, model serving runtimes, checkpoints, tokenization and context length, as well as GPU memory requirements and their impact on workload stability and job failures.
• Excellent written and spoken English, with the ability to hold a technical conversation with a customer and to write an unambiguous escalation.
• Experience with an ITSM tool such as Jira Service Management or ServiceNow, including queue and SLA discipline.
• Precise and structured documentation habits.
• Readiness to work 24/7 rotational shifts, including nights, weekends, and public holidays.

Preferred Skills

• Experience supporting a platform or SaaS product used by enterprise customers.
• Exposure to observability tooling such as Grafana or Prometheus, sufficient to read a dashboard and describe what it shows.
• Exposure to GPU-based or high performance computing workloads.
• Enough Python to read a customer’s script and identify an obvious error.
• Arabic in addition to English
• Certifications such as ITIL Foundation or Kubernetes Administrator (CKA)

Reporting To: Head of Technical Operations

Manages: None. This is an individual contributor role.