Forward Deployed AI Engineer

Riyadh, Saudi Arabia • Full-time • Frontier Context & mandate Echelon is a Saudi-born, sovereign technology company that brings leading global AI technologies to the Kingdom and the world, deploys them through its own forward deployed operations, and productizes Saudi-developed capability. Our engineers work on the hardest and most critical problems facing the Kingdom’s largest institutions. The role: deploying impact Embedded with customer teams, you own an engagement from the first conversation to its first system in production, delivering value, and then you repeat, with impact that grows over time. • Embed: Work on site with operators and executives, and run each engagement like a venture inside the customer. • Scope: Turn ambiguous, high-stakes problems into clear technical plans, and build first what creates most value. • Build: Design and deploy production-grade AI systems powered by LLMs, on architectures built to scale. • Drive adoption: Put systems in the hands of their users, measure the outcomes, and iterate until the impact is delivered. • Shape direction: Guide enterprise teams through AI adoption and set the technical direction of each engagement. Where we align AI and technology first • Engineering fundamentals: Strong proficiency in Python or TypeScript, and experience building reliable production systems with modern DevOps practices. • AI-native: Hands-on with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP or agent frameworks, and a strong understanding of AI system evaluation, debugging and observability. • Building AI systems: 1+ years building and deploying LLM-powered applications or AI agents in production, including RAG pipelines, tool use and multi-step AI workflows. 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. The seat • Location: Riyadh, Saudi Arabia • Package: A base salary with housing, transport and education allowances, 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 working code 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, test and debug code, and you have built something real with an LLM. • Where you are: From a first role to several years of shipping; fluent in Python, TypeScript or similar.

Embed with customer teams, own engagements from first conversation to production, turn ambiguous problems into technical plans, design and deploy production-grade AI systems powered by LLMs, drive adoption and measure outcomes, guide enterprise teams through AI adoption and set technical direction of each engagement.