Resident Engineer - Enterprise AI Platform

Resident, on-site role in Abu Dhabi.

We are seeking a Resident Engineer – Enterprise AI Platform to support the deployment, integration, administration, security, and day-to-day operation of an enterprise AI platform within a customer environment.

The role requires a combination of Kubernetes, Microsoft/Azure, cloud infrastructure, enterprise integration, cybersecurity, and Generative AI expertise. The engineer will work closely with infrastructure, cloud, cybersecurity, Microsoft, application and business teams, as well as the platform vendor’s technical teams.

Ideal candidate: a Cloud / Platform / DevOps Engineer with strong Generative AI knowledge, able to work across Kubernetes · Azure · Entra ID · Microsoft 365 / Graph · APIs · LLMs · RAG · AI Agents · Security · Production Support — technically strong enough to troubleshoot the underlying infrastructure while also understanding how modern enterprise AI solutions are designed, secured and operated.

• Configure and administer the enterprise AI platform.
• Support platform deployments in Kubernetes, private cloud, on-premises or hybrid environments.
• Configure and troubleshoot SSO, identity, integrations, AI models, agents, workflows and enterprise data sources.
• Provide day-to-day production support, troubleshooting, incident management and vendor escalation.
• Maintain platform documentation, architecture diagrams, runbooks and operational procedures.
• Support upgrades, patches, configuration changes and production releases.
• Work with customer infrastructure and cybersecurity teams to maintain a secure and reliable environment.

Kubernetes & Linux

• Strong hands-on Kubernetes experience: pods, deployments, services, ingress, secrets, RBAC, storage, networking and troubleshooting.
• Docker / containerization and Helm.
• Linux administration, shell commands, logs and resource troubleshooting.

Microsoft & Cloud

• Strong Microsoft Azure fundamentals. AKS experience is highly desirable.
• Microsoft Entra ID, SSO, SAML, OAuth/OIDC, service principals, RBAC and application registrations.
• Microsoft 365 and Microsoft Graph API.
• Azure networking, Key Vault, monitoring and private connectivity.

Infrastructure & Networking

• TCP/IP, DNS, HTTPS/TLS, certificates, firewalls, proxies, load balancers and routing.
• Ability to troubleshoot connectivity across application, network, infrastructure and security layers.

API & Integration

• REST APIs, JSON, OAuth, webhooks and API authentication.
• Experience with Postman, cURL and scripting. Python and/or PowerShell is desirable.

Generative AI & LLM knowledge

• LLMs and model architecture fundamentals; prompt engineering and structured outputs.
• RAG, embeddings, vector databases, semantic/hybrid search and reranking.
• AI agents, tool/function calling, workflows and MCP concepts.
• Model selection, inference, latency, context windows and token/cost management.
• AI observability, evaluation and hallucination mitigation.
• AI security risks including prompt injection, data leakage and excessive agency.
• Familiarity with leading model ecosystems such as OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral and DeepSeek, including the differences between commercial APIs, open-weight models and private/local deployment. Experience with Azure AI Foundry, AWS Bedrock, Google Vertex AI, NVIDIA AI/NIM or Hugging Face is advantageous.

AI Security & Governance

• Identity and least-privilege access; secrets and certificate management.
• Data protection and DLP; secure AI/LLM integration.
• Prompt injection and data leakage risks.
• AI governance, audit logging and access-controlled RAG.

• Bachelor’s degree in Computer Science, IT, Engineering or related field.
• 5+ years of relevant experience in Cloud, DevOps, Platform Engineering, Systems Engineering or Infrastructure.
• 2+ years hands-on Kubernetes experience.
• Strong Azure and Microsoft Entra knowledge.
• Enterprise API / integration experience.
• Practical knowledge of Generative AI, RAG and AI agents.
• Experience supporting production enterprise environments.
• Strong troubleshooting, communication and documentation skills.