AI Support Engineer

About AI Factory

The AI Factory is the product and technology arm of GovAI, responsible for:

• Building and operating sovereign AI platforms, models, and services across Abu Dhabi Government entities

• Scaling AI services from pilot to production

• Strengthening AI Operations to ensure:

  • Reliability

  • Governance

  • High-quality support for AI-powered workloads

Role Overview

Employment Type: Full-time

Work Arrangement: Onsite (Applicants based outside the UAE are required to relocate)

The AI Support Engineer is:

• The first line of operational support for AI platforms, AI models, APIs, and AI-enabled solutions

• Focused on supporting:

  • AI workloads

  • Model consumption

  • RAG pipelines

  • AI-driven applications running in production

• An AI-focused L1 operations role, aligned with AIOps practices (not a traditional IT helpdesk)

• Responsible for:

  • Triaging AI-related incidents

  • Monitoring model behavior and API performance

  • Supporting AI service integrations

  • Escalating issues to engineering, vendors, or platform teams

Key Responsibilities

AI Model & API Operations Support

• Support production AI model consumption (LLMs, embeddings, OCR, STT/TTS, inference APIs)

• Troubleshoot inference failures, latency spikes, malformed payloads, and API errors

• Diagnose authentication failures (OAuth, tokens, API keys, quota limits)

• Validate request structures and integration configurations

• Monitor token consumption trends and detect abnormal usage spikes

• Support quota management and controlled usage increases

RAG & AI Pipeline Operations

• Monitor RAG pipelines and retrieval workflows

• Troubleshoot embedding generation failures and indexing issues

• Identify ingestion failures affecting vector databases

• Validate document connector and data pipeline integrity

• Diagnose relevance or response degradation caused by configuration issues

• Escalate data-layer or infrastructure-level issues to DevOps support

AI Governance & Guardrail Monitoring

• Ensure AI service consumption complies with defined access controls and governance policies

• Validate rate limiting, usage policies, and guardrail configurations

• Detect abnormal usage patterns or policy violations

• Support enforcement of entity-level quotas and access restrictions

• Escalate governance breaches to appropriate stakeholders

Incident Triage & SLA Management

• Act as first responder for AI-layer incidents (P0–P3)

• Perform structured triage using logs, API traces, and monitoring dashboards

• Classify incidents based on severity and business impact

• Contain and mitigate AI service disruptions and coordinate with vendors when needed

• Escalate complex issues to L2/L3 engineering with complete diagnostic context

• Track incidents through full lifecycle and ensure SLA adherence

• Participate in Root Cause Analysis (RCA) for major AI service failures

Release Validation & Change Support

• Perform smoke validation after AI model updates or API releases

• Monitor regression risks following deployments

• Identify post-release anomalies and escalate early

• Support controlled rollout monitoring for new AI capabilities

Enterprise Integration & Connector Support

• Support integrations with enterprise systems (Microsoft 365, SharePoint, Teams, Oracle, Jira, etc.)

• Troubleshoot API integration failures, webhook errors, and data exchange issues

• Validate secure connectivity and authentication configurations

• Coordinate with DevOps support for infrastructure-related integration failures

Observability & Operational Monitoring

• Monitor AI API performance metrics (latency, error rates, throughput)

• Track token usage, consumption trends, and service availability

• Identify recurring failure patterns and propose preventive actions

• Maintain visibility dashboards for AI service health

Documentation & Knowledge Management

• Maintain AI troubleshooting runbooks and support playbooks

• Update known-issue repositories and FAQs

• Document recurring AI API and RAG-related issues

• Capture structured RCA documentation for major incidents

• Contribute to operational documentation for new AI services

• Handle ITSM/ticketing

Required Technical Skills

• Experience supporting REST APIs and API-based platforms

• Understanding of LLM consumption patterns (RAG, embeddings, inference APIs)

• Familiarity with authentication mechanisms (OAuth2, API keys, token-based access)

• Ability to troubleshoot using logs, traces, and monitoring dashboards

• Experience with monitoring tools (Azure Monitor, Dynatrace, Grafana)

• Basic understanding of cloud environments (Azure preferred)

• Familiarity with enterprise system integrations

• Understanding of rate limiting, quotas, and API governance

Experience

• 3–8 years in:

  • AI platform support

  • API support

  • SaaS support

  • Application operations

• Experience supporting AI/ML services or developer platforms preferred

• Exposure to regulated or government environments advantageous

• Experience working with external vendors and enterprise stakeholders

• Arabic speaker is a plus