AI Ops Engineer

At D4Insight, we celebrate human ingenuity. Alongside individuality, inclusivity and intraprenuership. And that's how we have defined and embraced the spirit of "Digital.Together". We craft, deploy, and manage bespoke services in CRM, data and AI, cybersecurity and consulting. Our solutions usher in impactful changes for industries in the banking, insurance, retail,telecom, and consumer products space. We have successfully helped retail chains enhance customer engagement and tier-1 insurance carriers extract risk insights from unstructured data. Our consultancy services help global banks mitigate data protection, regulatory compliance challenges, and cybersecurity threats. We are seeking for AI Ops Engineer to establish the operational backbone for enterprise AI platforms, enabling application teams to release AI products safely, repeatedly, and at scale. The role is responsible for production release discipline, LLMOps practices, deployment automation, operational governance, cost visibility, and self-service operating standards for AI-native delivery teams. Apply Now: [email protected]

Looking for a AI Ops Engineer at D4 Insight in Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates? This role focuses on the day-to-day work of a AI Ops Engineer.

Location: Abu Dhabi, UAE Experience: 7+ Years Role Overview We are seeking for AI Ops Engineer to establish the operational backbone for enterprise AI platforms, enabling application teams to release AI products safely, repeatedly, and at scale. The role is responsible for produc

Company Overview

At D4Insight, we celebrate human ingenuity. Alongside individuality, inclusivity and intraprenuership. And that's how we have defined and embraced the spirit of "Digital.Together". We craft, deploy, and manage bespoke services in CRM, data and AI, cybersecurity and consulting. Our solutions usher in impactful changes for industries in the banking, insurance, retail,telecom, and consumer products space. We have successfully helped retail chains enhance customer engagement and tier-1 insurance carriers extract risk insights from unstructured data. Our consultancy services help global banks mitigate data protection, regulatory compliance challenges, and cybersecurity threats.

Quick Details

• Salary Range: Not Applicable
• Job Type: Full-time
• Experience: 7+ Years
• Qualifications: Not Specified

Key Responsibilities

• Build standard release pipelines and promotion controls for AI applications, agents, platform services, and configuration changes.
• Ensure repeatable deployments with appropriate governance and release evidence.
• Implement controlled rollout, canary release, and rollback-readiness practices to reduce production risk.
• Embed operating controls for models and AI assets to support auditability and AI lifecycle management.
• Integrate AI quality checks, operational telemetry, dashboards, runbooks, and production-readiness criteria into delivery processes.
• Establish reusable operational standards and practices for AI-native teams.
• Provide visibility into AI workload consumption, including: Model usage, Token spend, Platform capacity, Quota management, Optimization opportunities.
• Convert proven operating patterns into reusable templates, release standards, onboarding guidance, and operational playbooks.

Requirements

• 7+ years of relevant experience.
• Strong production engineering background with cloud-native, AI, or high-scale API platforms in enterprise environments.
• Hands-on experience with CI/CD, GitHub Actions or equivalent automation, and environment management.
• Working knowledge of LLMOps, Telemetry, Release governance, and Production readiness.
• Experience with observability, change control, service reliability, and continuous operational improvement.
• Ability to collaborate with Platform Engineering, QA/SRE, Cybersecurity, Architecture, Product, and Delivery teams.

Benefits

• Visibility into AI workload consumption.
• Convert proven operating patterns into reusable templates, release standards, onboarding guidance, and operational playbooks.
• Collaborate with Platform Engineering, QA/SRE, Cybersecurity, Architecture, Product, and Delivery teams.