Basis

Tech / AI / Software

IntelligenceArchitect

$150–225k New York, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Intelligence Architect at Basis. Skills: Intelligence Architecting, Context Engineering, Agent Reasoning, Performance Measurement. Architecting and authoring our agents' context. Deciding what context our agents need, how it's structured, and what each layer says”

What You'll Achieve.

Deliver frontier intelligence; Treat context like a product; Ensure consistency across our agents; Each product team operates to the standards you set; Solve context issues when agent output isn't good enough; Orchestrating an intelligence whose ceiling rises with every model release, and whose capability compounds with every edit you make

Industry & Context.

Tech / AI / Software
Problems you'll solve

Reasoning about systems; Working from causes, not effects; Comfort in ambiguity; Holding many things at once

What They're Looking For.

Must Have

Writing as a craft, Reasoning about systems, Working from causes, not effects, Drawn to the frontier, Motivation by learning, Comfort in ambiguity, Holding many things at once

Nice to Have

Engineers and PMs who've drifted from building systems to questioning whether the system is doing the right thing, Philosophers who've spent years writing precise prose about systems no one else understood, Lawyers who write the kind of language other people have to follow, Accountants who appreciate language and want to shape the future of your profession, Editors and writers who treat structured prose as engineering, Academics tired of producing work that nobody acts on, Anyone who reads about what we're doing and recognizes the work as theirs

What You'll Do.

Architecting and authoring our agents' context

Deciding what context our agents need

and what each layer says

Writing the procedures

and system prompts they consume

Setting the standards for how procedures should be written

what makes a skill document load-bearing

and when context is ready to ship

Watching the agents at work and defining what's missing in the context when their output isn't good enough

Shaping what comes next by informing product decisions

How You'll Work.

Team & Collaboration

Work with accountants and engineers; Shared measurement work with product and eval teams

Communication Scope

Treat language as load-bearing; Write precise prose about systems; Write language other people have to follow; Write structured prose as engineering

Full Job Description

[https://app.ashbyhq.com/api/images/user-content/a3ff9955-736e-4a64-a923-c3c42b253641/17b03131-be3b-4bb8-9ad9-dbafd99fd465/image.png] ABOUT BASIS Basis builds real agents that do real work in the real economy. Our agents operate for hours at a time, performing end-to-end work for some of the largest accounting firms in the world. We recently raised $100M at >$1B valuation and are racing to deploy the most advanced applied ML at production scale. Our investors include: Khosla Ventures (Keith Rabois & Vinod Khosla), Accel (Miles Clements), Google Ventures, Nat Friedman & Daniel Gross, Adam D'Angelo, Jeff Dean, Jack Altman, Noam Brown, Kyle Vogt, Amjad Masad, Clem Delangue and many other operators/technical leaders. "Basis is on the frontier of building production-grade, long-horizon agents. They've pushed the limits of what we thought our models could do on real-world, economically valuable, complex accounting tasks. They've been a great collaborator in helping us shape what the future of agents looks like." — Prashant Mital, Applied AI Lead, OpenAI THE ROLE Every team building agents has access to the same models. Most of the attention goes to the product and its behaviors. The compounding work sits underneath: what the agent knows, how it reasons about its work, and how we measure whether it did the job well. At Basis, our agents autonomously perform real accounting work: reconciliations, tax preparation, audit procedures, financial analysis. Often, the quality of this work is not determined by which model we use. It is determined by the context those agents receive: the procedures that define what to do, the domain knowledge that defines how, and the evaluations that tell us whether it worked. To deliver frontier intelligence, we treat context like a product. The procedures, the skills, the system prompts. Each is owned, versioned, and held to a quality bar. Intelligence Architects build the coherent systems that construct our agents’ intelligence from disparate in

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