get hired at
Keenable
An independent web index built for AI agents, not for people
- —
- AZLCONAEA+3
- San Francisco
- AI
Open roles at Keenable
4 positions we're tracking, re-checked daily
- apply ↗
Member of Technical Staff, Engineering (full-time, remote, worldwide)
san francisco, usaSeniorfirst seen last month - apply ↗
Head of Product (full-time, remote, United States)
san francisco, usaSeniorfirst seen last month - apply ↗
Head of Revenue (full-time, remote, United States)
san francisco, usaSeniorfirst seen last month - apply ↗
GTM / Scientist Relations (full-time, remote, United States)
san francisco, usaMid-levelfirst seen last month
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- live
- +2h+2hrole spotted & verified1
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- day 3day 3you've applied~8
- day 7+day 7+hits the job boards250+
What Keenable is building
Keenable is building a second web index. Not a wrapper on someone else's results, not a reranker: its own crawler, its own index of more than 100 billion documents, and its own ranking stack, built from scratch on the premise that search designed for humans is the wrong shape for machines. The argument behind that is specific. A person types one query, glances at ten links, and stops. An agent working a task issues a query, reads the results, reasons about what it now doesn't know, and issues more queries, in a loop that can run hundreds of times for a single job. Human search is optimized for a fast first page and a satisfying click. Agent search is optimized for recall, freshness, cost per call at absurd volume, and returning content an agent can actually parse rather than a page it has to render. Those are different systems, and the incumbents' APIs were priced and shaped for the first one, which is part of why Google and Microsoft have been pulling back on offering them at all. The commercial shape is already public. The Search API sells at $4 per 1,000 requests pay-as-you-go for agent builders, dropping to $1 per 1,000 requests on dedicated capacity at 100+ requests per second for AI labs, with cloud or on-premises deployment and 100,000 requests free to start. Time Machine is in early access. A Web Query Language, for composing information across many sources in a single call rather than orchestrating hundreds of round trips, is the next product. Styskin's framing of the long game is the part worth sitting with: the behavioral signal Keenable collects comes from agents, not from human clicks. He describes it as a new flywheel, different from what Google learned from human behavior. If ranking quality compounds from usage data, and the usage is now machine usage, then the twenty-year advantage built on human clickstreams is not obviously the advantage anymore.
Why this matters
The founders are not making a first attempt at this. Andrey Styskin ran search at Yandex, one of the very small number of organizations on earth that built and operated a general web index competitive with Google, at a scale reported around 200 billion documents, and then went to Amazon as a director in its AGI group. Matthias Petri was a Principal Applied Scientist at Amazon AGI who built search infrastructure for Amazon's agents. This is a team that has already paid the cost of learning what breaks at index scale, which is the single hardest thing to hire for in this category. The market timing is that the incumbents have chosen not to serve it. Google and Microsoft have been retiring or restricting the search APIs that agent developers depended on, for the entirely rational reason that serving agents at volume cannibalizes the ad-supported product. That leaves a real gap, currently contested by Brave and Exa, and it is a gap where being an independent party with no search-ads business to protect is a structural feature rather than a talking point. Accel led, Conviction followed, and the angel list is a who's who of people who have personally operated large-scale data infrastructure at Amazon, ClickHouse, Databricks, Google and Snowflake. That is not thematic AI money. That is the specific group of people qualified to judge whether a claim about a 100-billion-document index is real.
Investors: Accel (Zhenya Loginov), Conviction, Angels: engineers and operators from Amazon, ClickHouse, Databricks, Google and Snowflake
Hiring outlook
Four roles are live on Keenable's own careers page, and the company has publicly stated it intends to roughly double its roughly 15-person engineering team by the end of 2026 using this round, expanding across both the Bay Area and Europe. That is explicit, dated hiring intent attached to a named headcount target.
Working at Keenable
Keenable is a AI company based in San Francisco, USA. For a AI company this size, the reality is opportunity to shape your role based on the company stage.
Most Keenable jobs are based in San Francisco, USA.
How to actually get hired at Keenable
Why applying the normal way doesn't work
Keenable uses an ATS, but referrals still come first. Cold applications aren't ignored — they're just behind referrals, sourced candidates, and recruiter picks.
Who to contact at Keenable
- Who decides
- the hiring manager
- Best channel
- LinkedIn or direct email
What to show them
Take a narrow slice of the web, a few thousand pages in one domain, and build the small honest version of what Keenable does at scale: crawl it, index it, dedup near-identical documents, and then evaluate ranking not by human relevance judgments but by whether an agent completes a multi-step task using the results. Publish where your eval disagrees with a human-relevance eval. That disagreement is the entire premise of the company and almost nobody has measured it.
A cold email that works at Keenable
What Keenable screens for
Accel's Zhenya Loginov led a $26M seed into a fifteen-person company with no consumer product, which only makes sense as a bet on one thing: that whoever owns an independent index at agent scale sits underneath the entire agent economy and charges rent, the way Stripe sits underneath payments. Conviction's participation is the second-order tell, since that fund's whole thesis is picking the infrastructure layer of the agent stack early. The hiring window is narrow and unusually open at the same time. Narrow because a company doubling from fifteen makes roughly fifteen decisions, and each one is a founder decision. Open because the single engineering listing is remote worldwide, with no location filter, which is nearly extinct at companies with this much capital. If you have ever built or operated a crawler, an inverted index, or ranking evaluation at scale, this is the rare listing where that specific and otherwise unmarketable experience is the entire job.
Don't send a generic CV to Keenable. Mirror the job posting's language to get past automated screening.
Don't make these mistakes
Andrey ran a general web index at roughly 200 billion documents in direct competition with Google, then went and did search infrastructure at Amazon AGI. Telling him you are excited about RAG, or that you have built agents on top of a search API, is describing the customer, not the work. The same goes for generic distributed-systems enthusiasm; he has hired hundreds of those people. What actually lands is a specific retrieval failure you have measured: a freshness gap on a class of pages, a dedup strategy that collapses near-identical documents it shouldn't, a spam pattern that survives ranking, an eval that shows a benchmark disagreeing with real agent success. Bring the number and the reproduction, not the enthusiasm. Same warning applies to pitching Matthias on applied ML generally; he was a Principal Applied Scientist at Amazon AGI, so the bar for what counts as an interesting retrieval result is somewhere above the current literature.
Mistakes that kill Keenable applications
At people, a copy-paste CV is immediately obvious. It's an instant no.
Lead with their problem, not your ambition. Keenable is focused on The founders are not making a first attempt at this — show you understand that.
Don't apply and wait. The median AI application gets no response ever. One follow-up at day five roughly doubles reply rates.
Applying to Keenable? Get the contact, not the form.
The Keenable interview process
We don't yet have verified candidate reports for Keenable. What follows is the typical process for a -person AI company, so treat it as a model, not confirmed detail.
Interview stages
- 1
Recruiter Screen
Phone or video · 30 min
What it testsBasic qualification and logisticsUsually run byRecruiter or HR - 2
Hiring Manager Interview
Video call · 45 min
What it testsRole fit and experience deep-diveUsually run byHiring manager - 3
Technical/Functional Round
Video call · 60 min
What it testsSkills assessment and problem-solvingUsually run byTeam members - 4
Final Round
In-person or video · 60 min
What it testsCulture fit and cross-functional alignmentUsually run bySenior leadership
Keenable take-home assignment
Keenable includes a take-home exercise in their interview process. For AI roles, this typically involves a practical problem that takes 2-4 hours. Focus on clean, working code over premature optimization. They're evaluating how you think and communicate, not just the solution.
Keenable interview timeline
At 14 days, Keenable's process is about average than typical for AI (14 days at this size).
Interviewed at Keenable?
Tell us how it went: stages, questions, timeline. Takes 90 seconds and it's how this page stays accurate for the next person.
Keenable jobs, frequently asked questions
How many jobs does Keenable have open?
Keenable currently has 4 open roles, last verified October 14, 2026.
Does Keenable hire remotely?
All current Keenable roles are based in San Francisco, USA.
What roles is Keenable hiring for?
Keenable is hiring across Engineering, Other, Data. The most recent opening is Member of Technical Staff, Engineering (full-time, remote, worldwide).
How do I apply for a job at Keenable?
Apply directly through the links above, or read our guide on how to actually get hired at Keenable.
Does Keenable respond to cold emails?
We're still collecting cold email data for Keenable.
Who is the hiring manager at Keenable?
At this size, hiring is usually run by the hiring manager.
How competitive is it to get hired at Keenable?
Expect 100-250 applicants in the first two weeks for AI roles at this size. Apply within 72 hours for best odds.
How many rounds is the Keenable interview?
4 stages: Recruiter Screen, Hiring Manager Interview, Technical/Functional Round, Final Round.
Is the Keenable interview hard?
It concentrates on technical depth and system design rather than abstract puzzles. The stage candidates find hardest is Technical Interview.
Does Keenable give a take-home task?
Yes, Keenable includes a take-home assignment.
How long does Keenable take to get back to you?
Around 14 days across the full process.
What should I prepare for the Keenable interview?
Study technical depth and system design. At this size (), they care about self-sufficiency over textbook knowledge.
Where is Keenable based?
Keenable is headquartered in San Francisco, USA.
Get Keenable roles before they're posted
A role stays uncontested for about four days. Here's the window, and where we put you in it.
From $5.99/week, cancel any time.
- live
- +2h+2hrole spotted & verified1
- +4h+4hyou get the alert1
- day 3day 3you've applied~8
- day 7+day 7+hits the job boards250+
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