Echelon
Requirements
The role requires 8+ years of experience building reliable production systems and 5+ years specifically in deploying AI/ML and LLM-powered applications. Candidates must possess expert proficiency in Python or TypeScript and a strong background in modern DevOps practices and AI system observability.
Job Summary
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: Expert proficiency in Python or TypeScript, and 8+ years 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: 5+ years building and deploying AI/ML and 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 the 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: Principal level, with 8+ years of shipping and a record of leading complex deployments end to end; fluent in Python, TypeScript or similar.
Responsibilities
You will own the end-to-end engagement process, from initial conversation to deploying production-grade AI systems within customer environments. You are responsible for turning ambiguous, high-stakes problems into technical plans and driving AI adoption through hands-on collaboration with operators and executives.
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