Data Quality & AI Operations Manager
Listed on 2026-09-29
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IT/Tech
AI Evaluation, Data Annotation/ AI Labeling, AI Business & Operations, AI Engineer (Applied/Software)
About Extend: Extend is a Saudi cultural intelligence and advertising company, operating since 2012, serving the Kingdom's leading brands and institutions across experiences, media, and publishing. We are building Extend CIP, the Cultural Intelligence Platform: one place to plan, manage, and measure all media activity, earned and paid, spanning media and influencer buying and a brand monitoring suite, with cultural intelligence and AI at its core.
About Extend: Extend is a Saudi cultural intelligence and advertising company, operating since 2012, serving the Kingdom's leading brands and institutions across experiences, media, and publishing. We are building Extend CIP, the Cultural Intelligence Platform: one place to plan, manage, and measure all media activity, earned and paid, spanning media and influencer buying and a brand monitoring suite, with cultural intelligence and AI at its core.
Role SummaryThe role:
Own content and data operations for the Extend platform. Build a leaner, more accurate profiling process and use AI fine tuning to progressively replace manual annotation with automation. You own the evaluation and data feedback loop and lead the content operations team. Success is measured by golden-set accuracy and profile automation rate.
Build and maintain golden sets and eval suites; define acceptance criteria for each AI Admin iteration
Own the data side of AI Admin iterations: curate training and evaluation data, run benchmarks, analyze failure modes, and partner with Shanghai engineering on fine tuning and deployment
Design the human-in-the-loop (HITL) mechanism: define the boundary between human review and auto-approval, and feed human corrections back into prompts, eval sets and training data
Author and maintain Arabic/English labeling guidelines; adjudicate edge cases requiring cultural and linguistic judgment
Lead the content operations team with end-to-end ownership of annotation operations: rater training, workflows, throughput and quality SLAs
Establish and track a quality metrics framework: accuracy, automation rate, inter-annotator agreement, cost and turnaround per profile
Fluent in Arabic, with strong knowledge of the Arab world's media, brands, publishers and cultural context
Hands-on experience with AI agent / LLM systems: eval design, golden sets and model feedback loops; conversant in fine tuning concepts (SFT, RLHF, prompt iteration) without needing to train models yourself
2+ years in AI data operations or applied AI quality, from a data labeling company (Scale AI, Surge, Appen, Sama, Invisible, Labelbox), an in-house annotation team at an AI company, or an AI product team
Comfortable collaborating across Riyadh and Shanghai time zones
LLM-assisted labeling automation, taxonomy design, social or media data experience.
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