Head of Applied AI

Echelon; Riyadh; In loco; SAR 903.000 - 1.305.000; Tempo pieno

Descrizione del lavoro

Echelon seeks a senior engineering leader to own applied AI engineering across engagements. You will define architecture, lead forward deployed engineers, and ensure production-grade quality from prototype to live systems.

You will also guide security, data residency, and scalable delivery with partners and customers. Based in London with regular Riyadh presence, you will mentor teams, drive enterprise-grade AI solutions, and maintain executive credibility while balancing technical and

Competenze

• 6+ years in engineering leadership with teams shipping production systems.
• Experience leading AI-based product/platform deployments for enterprises or government.
• Strong ability to translate customer needs into scalable engineering solutions.

Mansioni

• Define the technical direction for every engagement: architecture, model and partner choices.
• Build and lead engineers, design pods, and create scalable engineering culture.
• Own the technical quality from prototype to production and manage risk."
• Support sales with architecture reviews, demos and solution design for CIOs/CISOs.
• Set security, data residency standards and ensure compliance across deployments.
• Shape platform roadmap and repeatable delivery patterns with partners and customers.
• Transfer capability with documentation, monitoring, and handover to customers.

Conoscenze

Engineering leadership

AI systems

Distributed systems

Enterprise delivery

Executive communication

Pre-sales & architecture

Python

TypeScript

Formazione

PhD in AI, ML or CS (advantage)

Strumenti

LLMs

Descrizione del lavoro

The Role: Leading Applied AI

Reporting to the Managing Director, you own Echelon’s applied AI engineering: the team, the technology and the technical quality of everything we deploy. You own the customer and build what is deployed against their most critical workflows, running every engagement as one team with the Head of AI Transformation.

• Technical direction: Define the technical direction of every engagement: architecture, model and partner choices, and the build, partner or buy decisions behind them.

• Build the organisation: Hire and lead forward deployed engineers and their leads; design pods sized to signed demand, the hiring bar, the career paths and an engineering culture people want to join, with a deliberate pipeline of engineering talent in the region.

• Answer for delivery: Own the technical quality of every deployment from prototype to production, and sign off scope, architecture and technical risk before Echelon commits to a customer. Stay close enough to live systems to review designs, unblock critical issues and lead incident reviews.

• Support the sale: Be the senior technical counterpart in strategic pursuits: architecture, security and data-residency reviews, demos and solution design with customer CIOs and CISOs. Shape how engagements are scoped and priced.

• Set the standards: Set how Echelon builds, secures and operates AI systems, with the security and data baseline every deployment meets, aligned with data-protection and security regulations, and hold delivery partners to it.

• Transfer capability: Make sure every deployment leaves the customer able to run it: documentation, evaluations, monitoring, training and a clean handover.

• Shape the platform: Work with the platform lead to shape Echelon’s platform roadmap and its evolution over time, bringing repeated delivery patterns and customer needs back from the field.

• Shape the ecosystem: Lead the technical relationship with technology partners and model providers across Echelon’s engagements.

Where We Align

AI and Technology First

• Leadership record: You have 6+ years in engineering, including building and leading teams that ship production systems, as a senior leader in an AI company, a forward deployed business, or as a technical founder.

• Builder’s record: You have taken a product or platform from zero to real users at scale, and know the difference between a demo and a system an enterprise depends on.

• AI-native depth: Hands-on with LLMs, agent frameworks, MCP, retrieval and evaluation, with a clear view of how to make AI systems observable, safe and reliable at scale. You still go hands-on when it matters.

• Systems at scale: Command of distributed systems, data engineering, and cloud and on-premise infrastructure under strict data residency and security constraints.

• Enterprise delivery: You have led complex deployments for large enterprises or government, including technical pre-sales, scoping and the commercial trade-offs behind them.

• Executive credibility: Customer technology leaders, partners and investors trust your judgement, and you can explain a trade-off to an engineer and to a board on the same day.

Strong Advantage

• Academic depth: A PhD in AI, Machine Learning or Computer Science.

• Regional experience: Delivery in Saudi Arabia or the GCC, ideally in the public sector or regulated industries, with working knowledge of PDPL, NCA and SDAIA frameworks.

• Arabic & multimodal: Experience building Arabic NLP, speech or multimodal systems. Arabic language is a plus.

• Open-weight models: Fine-tuning, post-training or serving open-weight models on private or on-premise infrastructure.

• Partnerships: Experience leading technical relationships with model providers, cloud providers or technology partners.

Our Values

• Customer first: You measure your work by customer outcomes, and prioritise accordingly.

• Ownership mentality: You own outcomes end to end. When something breaks or stalls, you treat it as yours to fix.

• Clear communicator: You explain complex systems simply, to operators and executives alike, and make the value of your work visible.

• Comfortable with ambiguity: You make progress with incomplete information, partial data and unfamiliar environments, and you enjoy solving problems where there is no structure yet.

• Long-term builder: You invest in Echelon’s long-term success, bringing field insight back into our strategy and operations.

• Builds others: You measure yourself by the engineers you develop and the capability you leave behind with customers.

The Seat

• Location: London, with regular time in Riyadh, or Riyadh

• Reports to: The Managing Director

• Travel: Regular time on customer sites across the region and with partners abroad.

• Package: A base salary, performance bonus, medical cover, and equity through the employee equity programme. Terms are shared at offer stage.

How We Work

You start from the problem, not the tool. You meet an unclear brief or a broken environment with energy and a plan.

• Curiosity: You learn how the work really happens on site and keep learning as the stack moves.

• Speed: You move from brief to a working system quickly and do not wait for perfect conditions.

• Rigour: You reproduce before you fix, test what you ship and can explain every choice.

• Confidence & humility: You challenge and accept challenge, and change your view on evidence, without ego.

• Autonomy: You decide with incomplete information and own it; from an outcome, you organise the work yourself.

• Resourcefulness: Missing access, partial data, an unfamiliar codebase: you find a way with what is available.

• Situational leadership: You lead when the moment calls for it, and follow when someone else has the better call.

• A force multiplier: Your reviews, patterns and documentation make the whole bench faster.

• AI-native depth: AI tools are part of how you write, review and debug code and how you run the organisation, and you have built something real with an LLM.

• Where you are: A senior engineering leader who stays close to the code: fluent in Python, TypeScript or similar, and able to review what ships