AI Engineer

What We're Looking For

As an AI Engineer at Scope Labs, you won't just be fine-tuning models in isolation. You'll be embedded directly with our startup customers, designing and shipping the AI systems that power their products from day one. We're looking for someone who thrives at the intersection of applied ML, systems thinking, and customer partnership; someone who can take an ambiguous problem on Monday and have a working prototype in production by Friday.

This role is for a builder who is equally comfortable digging into a customer's production environment and whiteboarding a new AI workflow with their engineering lead. The specifics of what we're building are still under wraps, but if you're excited by the idea of being one of the first people to bring genuinely new technology into the hands of fast-moving teams, this is that role. You'll represent Scope Labs in the field, which means operating with autonomy, exercising strong judgment under ambiguity, and holding yourself accountable for outcomes, not just outputs.

Responsibilities

Own the full technical customer lifecycle. From initial deployment through activation and ongoing utilization, you are the person who makes sure our customers are actually getting value, not just access.
Identify and champion high-impact use cases. Work closely with startup engineering teams to understand their workflows, identify where AI can meaningfully accelerate them, and get those integrations shipped.
Be the voice of the customer internally. Bring patterns, friction points, and product insights back to our Product and Engineering teams, helping shape the roadmap based on what you're seeing in the field.

Preferred Qualifications

3+ years building and shipping ML/AI systems in production, whether as an ML Engineer, AI Engineer, or Software Engineer with applied AI experience. Former technical founders are strongly encouraged to apply.
Strong proficiency in Python and/or TypeScript, with hands-on experience building and deploying LLM-based applications, agents, or AI pipelines.
Deep familiarity with the modern AI stack — including model APIs, RAG, fine-tuning, evals, and orchestration frameworks — and a track record of turning that into working products.
Experience in a customer-facing or client-embedded role, such as Forward Deployed Engineer, Solutions Engineer, or consulting, is a plus.
High agency with comfort operating in ambiguous environments and limited direction.
Strong communication skills across audiences, from senior engineers to non-technical founders.
Team-first attitude with the ability to juggle multiple customer engagements simultaneously.