Head of Applied AI

About the Role
In this role, you will be responsible for owning applied AI engineering, encompassing the entire team and the quality of technology deployments. Reporting to the Managing Director, you will collaborate closely with the Head of AI Transformation to address customer needs and optimize the deployment of solutions tailored to critical workflows.

Responsibilities

• Technical direction: Define the technical direction for each engagement, guiding architecture, model selection, and strategic build or buy decisions.
• Build the organization: Hire and lead forward deployed engineers, designing pods according to demand, setting hiring standards, career paths, and fostering an attractive engineering culture.
• Answer for delivery: Ensure technical quality in every deployment, managing the transition from prototype to production, and reviewing scope and architecture to mitigate risk. Stay connected to live systems to oversee designs, troubleshoot issues, and lead incident reviews.
• Support the sale: Serve as the senior technical counterpart in strategic pursuits, conducting architecture, security, and data-residency reviews, as well as solution design with customer CIOs and CISOs. Help shape engagement scopes and pricing.
• Set the standards: Establish the expectations for building, securing, and operating AI systems, driving compliance with data protection and security regulations across all deployments and partnerships.
• Transfer capability: Ensure that customers are equipped to manage deployments autonomously, including comprehensive documentation, evaluations, monitoring, training, and handover processes.
• Shape the platform: Collaborate with the platform lead to influence the company’s platform roadmap and facilitate ongoing improvements based on field insights and customer needs.
• Shape the ecosystem: Lead technical relationships with technology partners and model providers throughout various engagements.

Where We Align
AI and Technology First

• Leadership record: 6+ years in engineering with experience in building and leading teams that deliver production systems, ideally in an AI-focused company, a forward-deployed business, or as a technical founder.
• Builder’s record: Proven track record of taking a product or platform from inception to a user base at scale, understanding the differences between a demo and an enterprise-level system.
• AI-native depth: Proficient hands-on experience with LLMs, agent frameworks, and data management tools, with the capability to ensure AI systems are observable, secure, and reliable at scale.
• Systems at scale: Comprehensive knowledge of distributed systems, data engineering, and infrastructure in both cloud and on-premise environments, particularly with stringent data residency and security constraints.
• Enterprise delivery: Experience leading complex deployments for large organizations or government entities, including aspects of technical pre-sales, project scoping, and understanding the commercial trade-offs involved.
• Executive credibility: Able to gain the trust of customer technology leaders, partners, and investors, effectively communicating technical trade-offs to both technical and non-technical audiences.

Strong Advantage

• Academic depth: A PhD in AI, Machine Learning, or Computer Science.
• Regional experience: Experience delivering projects in Saudi Arabia or the GCC, especially within public sector or regulated industries, familiar with PDPL, NCA, and SDAIA frameworks.
• Arabic & multimodal capabilities: Experience developing Arabic NLP, speech, or multimodal systems; proficiency in Arabic is a plus.
• Open-weight models: Expertise in fine-tuning and serving open-weight models on private or on-premise infrastructure.
• Partnerships experience: Proven record of leading technical relationships with model providers, cloud service providers, or other technology partners.

Our Values

• Customer first: Success is measured by customer outcomes, driving prioritization accordingly.
• Ownership mentality: Taking full responsibility for outcomes, addressing issues proactively.
• Clear communicator: Simplifying complex systems for diverse stakeholders and showcasing the value of contributions.
• Comfortable with ambiguity: Making progress in uncertain environments while solving undefined problems.
• Long-term builder: Investing in the future success of the company and integrating field insights into strategy and operations.
• Builds others: Valuing personal success in the growth and capability development of the engineers and customers involved.

The Seat

• Location: London, with regular travel to Riyadh or based in Riyadh.
• Travel: Frequent on-site visits to customer locations across the region and with partners abroad.
• Package: Compensation includes a base salary, performance bonus, medical coverage, and equity through the employee equity program. Specific terms will be communicated during the offer stage.

How We Work
You approach challenges by identifying the root problem rather than focusing solely on tools.

• Curiosity: Continuously learning how work is conducted on-site and adapting as required.
• Speed: Transitioning quickly from problem identification to delivering functional systems without waiting for ideal conditions.
• Rigour: Ensuring thorough testing and documentation of every choice made during development.
• Confidence & humility: Open to challenges and capable of adapting perspectives based on evidence.
• Autonomy: Making informed decisions in ambiguous situations and independently organizing work.
• Resourcefulness: Overcoming obstacles with limited data or access to find effective solutions.
• Situational leadership: Flexibly leading or following as the circumstances require.
• A force multiplier: Enhancing team efficiency through robust reviews, established patterns, and comprehensive documentation.
• AI-native depth: Utilizing AI tools in processes for code development and organizational management while having practical experience developing with LLMs.
• Technical fluency: Being a senior engineering leader with a strong background in languages such as Python, TypeScript or similar, capable of reviewing technical outputs.