Careem is building the Everything App for the greater Middle East, making it easier than ever to move around, order food and groceries, manage payments, and more. Careem is led by a powerful purpose to simplify and improve the lives of people and build an awesome organisation that inspires. Since 2012, Careem has created earnings for over 2.5 million Captains, simplified the lives of over 70 million customers, and built a platform for the region’s best talent to thrive and for entrepreneurs to scale their businesses. Careem operates in over 70 cities across 10 countries, from Morocco to Pakistan.
Role Mission
Lead the end-to-end productization of a future-proof, AI-native Growth Engine that dynamically orchestrates customer value interventions across acquisition, graduation churn prevention, cross-sell, upsell, and retention. This role is pivotal to Careem’s ambition to build self-optimizing, LLM-augmented growth loops integrated into our product fabric.
Key Responsibilities
- Architect and lead the product development of the Next Best Action Engine (NBA), integrating real-time signals, predictive models, reinforcement learning loops, and LLM-based personalization layers.
- Translate customer behavior insights into programmable customer journeys, stitched across product surfaces, CRM, and marketing automation platforms.
- Define infrastructure and experience-level requirements to enable autonomous treatment orchestration, including fallback logic, response explainability, and agentic task flows.
- Partner with ML/LLM teams to integrate hybrid AI stacks—combining scoring models, embedding-based retrieval, and agentic flows—to drive personalized actions at scale.
- Own the roadmap for end-to-end system integration into customer data platforms (CDPs), notification systems, experiment orchestration layers, and analytics observability pipelines.
- Collaborate closely with marketing, engineering, data science, and ops to scale interventions across acquisition, engagement, and monetization loops.
Ideal Candidate Profile
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5+ years of product leadership experience, with a deep focus on AI-powered growth systems, personalization infrastructure, or lifecycle automation at scale.
- Experience leading the development of Next Best Action engines, personalization platforms, or autonomous lifecycle systems in B2C environments.
- Strong working knowledge of LLMs, retrieval pipelines, memory architecture, and prompt engineering principles.
- Proven experience integrating products with CDPs, mar-tech stacks (Braze, Iterable), real-time event buses, and segmentation frameworks.
- Experience leading cross-functional pods comprising ML/LLM engineers, infra architects, and marketing operators.
- Fluency in AI/ML workflows including propensity modeling, supervised learning, clustering, causal impact analysis, and LLM-agent design patterns.
- Strong belief in productized intelligence—AI systems that can autonomously adapt and drive growth outcomes without manual tuning.
