AI Engineering Manager: Marketing & Personalization AI

Job Description Roles & Responsibilities As an AI Engineering Manager, you will lead the team behind Unifonic's marketing and personalization AI, building the intelligence that determines who to engage, through which channel, at what time, and with what message. You will own the development and delivery of AI capabilities spanning audience segmentation, propensity and churn prediction, next-best-action and channel recommendations, send-time optimization, campaign optimization, and generative AI for personalized content. These systems directly drive conversion, engagement, and customer retention for the brands we serve. This is a hands-on leadership role that combines people management with technical ownership. You will lead, mentor, and grow a team of talented AI engineers while actively contributing to architecture, technical design, code reviews, performance optimization, and proof-of-concept development. You will ensure the team delivers scalable, production-grade AI solutions, foster engineering excellence, and cultivate a culture of collaboration, innovation, and continuous learning. Help us shape the future of communications by: Serving as the technical owner on AI model design, architecture, and integration for marketing and personalization use cases across the Unifonic product ecosystem. Owning the technical roadmap for personalization AI, recommendation and next-best-action engines, customer segmentation and propensity models, campaign and send-time optimization, and generative AI for content personalization. Leading the evaluation, selection, and implementation of AI/ML frameworks, tools, and best practices, ensuring scalability, robustness, and maintainability. Participating in hands-on coding, solution prototyping, and code reviews to maintain high-quality standards and guide the team through complex technical challenges. Overseeing and refining the AI development lifecycle, including model training, validation, deployment, experimentation (A/B and uplift testing), and ongoing improvement. Leading a team of AI engineers, providing mentorship, regular feedback, and career development support. Defining clear performance expectations, conducting performance reviews, and identifying growth opportunities for team members. Fostering a positive, inclusive, and high-performance team culture that encourages innovation, continuous learning, and collaboration. Collaborating with recruitment and HR to identify, attract, and retain top AI engineering talent, ensuring the team s ongoing growth and success. Working closely with the Director of AI Development, Product Managers, Designers, Data Scientists, and other Engineering leaders to translate business requirements into technical roadmaps and actionable engineering plans. Ensuring seamless integration of AI capabilities into existing and future products, partnering with platform, infrastructure, and DevOps teams to optimize deployment and operations. Communicating technical topics effectively to non-technical stakeholders, making recommendations and reporting progress, risks, and opportunities. Implementing and continuously improving the development processes, standards, and tools that drive efficiency, reliability, and scalability. Ensuring adherence to best practices in model governance, performance monitoring, and compliance with relevant data privacy and security regulations, including regional data residency requirements. Monitoring engineering metrics and KPIs, leveraging data-driven insights to improve development velocity, code quality, and team efficiency and connecting model performance to marketing outcomes such as conversion, engagement, and retention. Desired Candidate Profile Bachelor or master degree in Computer Science, Engineering, or a related field. 8+ years of software development experience with at least 3 years focused on AI/ML engineering and related technologies. Demonstrated experience building and shipping marketing or personalization AI in production recommendation systems, customer segmentation, propensity/churn/LTV modeling, real-time decisioning, or campaign optimization with measurable impact on business KPIs. Proven track record of leading, mentoring, or managing engineering teams, preferably in high-growth or innovative tech environments. Hands-on experience with a range of AI/ML frameworks (e.g., TensorFlow, PyTorch), advanced modeling techniques (NLP, LLMs and generative AI, recommendation and ranking systems), and production-grade model deployments. Solid grounding in experimentation and measurement, A/B testing, uplift modeling, and evaluating model impact on conversion, engagement, retention, and ROAS. Proficiency in Python, cloud platforms (e.g., OCI, AWS, GCP), CI/CD workflows, and modern software engineering practices. Excellent communication and interpersonal skills, with the ability to motivate teams and build productive cross-functional relationships. A strategic and solution-oriented mindset, capable of balancing technical depth with big-picture thinking. Experience with MarTech ecosystems, customer data platforms (CDPs), campaign orchestration, marketing automation, or CPaaS/omnichannel messaging platforms is preferred Experience applying LLMs to marketing use cases, content generation, conversational commerce, or agentic customer journeys including fine-tuning and retrieval-augmented generation (RAG), ideally within the Hugging Face ecosystem (Transformers, PEFT, tokenizers, and the model hub) is preferred Exposure to Rust for performance-critical AI services, such as low-latency inference, real-time decisioning, or high-throughput data pipelines is preferred. Arabic NLP experience or familiarity with the MENA market is preferred. Experience scaling teams and systems in a high-growth SaaS environment is preferred. Craft & Toolkit: Machine Learning & Deep Learning Generative AI & LLMs Recommendation Systems & Personalization Customer Segmentation, Propensity & Churn Modeling Python TensorFlow / PyTorch Hugging Face & RAG AWS / GCP / OCI MLOps & CI/CD A/B Testing & Model Evaluation Software Architecture & System Design AI Engineering Leadership & Team Management Character Traits: Analytical thinking and problem-solving approach problems clearly, use data, and find solutions. Ownership and accountability take responsibility and follow projects through to completion. Communication explain ideas clearly and listen to others across teams. Collaboration work well with others and support team goals. Adaptability and learning adjust to change and keep learning new skills or tools. Mentorship and knowledge sharing help others grow and share what you know. Resilience stay calm under pressure and handle setbacks constructively. Quality and attention to detail do work carefully and strive for improvement. Advocacy and innovation encourage best practices, efficiency, and new ideas Company Industry IT - Software Services Department / Functional Area IT Software Keywords AI Engineering Manager: Marketing & Personalization AI Get real-time job updates only on our App