AI Engineering Manager: Marketing & Personalization AI

Proudly recognized as a Great Place to Work®, we are an AI-native customer experience platform purpose-built for emerging markets. With more than 25 years of conversational AI research and development, we serve over 5,000 enterprises across MENA and are pioneering sovereign, agentic AI through our Agentic Studio platform. As the category takes shape, the way Unifonic is perceived — by buyers, analysts, media, and the broader market — is a strategic asset. This role owns that perception.

We thrive on creativity, collaboration, and fun, where every idea is welcomed and celebrated. As shareholders in the company, we’re more than just communicators—we’re innovators shaping the future together. We are Unifones. Join us and be part of something extraordinary!

Meet the team!

Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic’s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.

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.