Role: Engineering Manager

Location: Abu Dhabi, United Arab Emirates

Company: AI71

About Us

AI71 is an innovative applied research team pushing the boundaries of Generative AI to create impactful and responsible solutions for knowledge workers. We work closely with industry leaders and researchers from the Technology Innovation Institute (TII) to develop groundbreaking AI products that are shaping the future of work. Our mission is to build powerful AI agents that help businesses thrive.

About the Role

We are looking for an experienced Engineering Manager to lead a multidisciplinary team responsible for the full engineering pipeline—spanning front-end, back-end, and AI development. In this role, you will provide leadership across the technical stack, ensuring smooth collaboration between teams and removing roadblocks that may arise in the development process. You’ll oversee the delivery of high-quality software and AI solutions while ensuring best practices are followed throughout the engineering lifecycle.

As an Engineering Manager, you will guide technical execution, mentor engineers, and work closely with cross-functional teams to ensure we meet our ambitious goals. You will review code, establish development standards, and facilitate a culture of continuous improvement and excellence.

Key Responsibilities

• Technical Leadership: Oversee the entire engineering pipeline (front-end, back-end, AI), ensuring effective collaboration and high-quality delivery across all stages of development.
• Mentorship & Team Development: Lead, mentor, and grow a team of engineers by providing technical guidance, feedback, and support for personal and professional development.
• Project Execution & Delivery: Oversee the end-to-end development lifecycle, from concept to deployment. Ensure timely delivery of AI models, APIs, and full-stack applications. Work with product managers to translate business requirements into technical solutions.
• Remove Technical Blockers: Act as a point of escalation for the development team, quickly identifying and resolving technical issues or bottlenecks that could impede progress.
• Code Quality & Best Practices: Conduct code reviews to ensure adherence to best practices, high-quality code standards, and maintainable solutions. Foster a culture of continuous learning and improvement.
• Collaboration with Cross-functional Teams: Work closely with product, design, and AI teams to ensure alignment between technical delivery and business goals. Act as a technical liaison between teams to ensure clear communication and collaboration.
• Architectural Oversight: Ensure that the technical architecture of systems across front-end, back-end, and AI layers is scalable, maintainable, and well-integrated.
• Continuous Improvement: Promote best practices in software engineering and AI development, driving initiatives around code quality, testing, and overall process improvements to optimize development workflows.
• Performance Management: Track and report on team performance, progress, and project timelines, ensuring timely delivery while maintaining high standards of technical excellence.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 10+ years of experience in engineering, with at least 3 years in a leadership or managerial role.
• Solid experience across the full engineering stack (front-end, back-end, and AI), with hands-on technical expertise in both.
• Proven experience in code reviews, ensuring adherence to best practices, and helping teams maintain high-quality standards.
• Demonstrated experience in removing technical roadblocks and helping teams overcome complex challenges in a fast-paced environment.
• Experience with Agile or Scrum methodologies and leading engineering teams in these frameworks.

Preferred Qualifications:

• Master’s degree in Computer Science, AI, Engineering, or a related field.
• Extensive experience with Generative AI technologies, including large language models (LLMs) and natural language processing (NLP).
• Familiarity with cloud platforms (AWS, Azure, GCP) and distributed systems.
• Experience in both SaaS and enterprise environments.
• Strong leadership skills with a track record of developing high-performing engineering teams.
• Knowledge of ethical AI practices and an interest in ensuring AI solutions are built responsibly.