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RIDGE AI

AI-native embedded analytics for B2B SaaS, browser-native dashboards and conversational AI data agents deployable in hours, not months

3 open rolesPre-Seed · $2.6M<50 peopleSeattle

Last verified August 17, 2026 · Updated daily

What RIDGE AI is building

Every B2B SaaS product eventually needs to show its customers what is happening with their data inside the product. Usage analytics. Performance dashboards. ROI metrics for the customer success team to cite during renewals. The standard approach is to build these dashboards custom, which diverts engineering for weeks or months, produces something that is fragile, hard to update, and never quite what the customer actually wanted. The alternative is an embedded analytics vendor like Looker Embedded or Tableau Embedded, which require extensive integration work, carry heavy licensing costs, and produce dashboards that are interactive enough to be pretty but not fast enough to be genuinely analytical. Ridge solves this differently. The platform is built on Jeff Heer's open-source Mosaic framework, which uses DuckDB running natively in the browser and WebAssembly to process data directly on the client side rather than on a server. The practical consequence: sub-second interactivity on datasets with millions of rows, at no cloud compute cost to the software company embedding the dashboard. Teams integrate with Ridge and ship an interactive, customer-facing dashboard in hours. On top of the dashboard, Ridge adds an AI data agent that lets customers ask follow-up questions in natural language and get immediate answers. The combined product is what Ridge calls a "ridge", a dashboard and a data agent sharing a common dataset.

Why this matters

The embedded analytics market has a technical debt problem so large that the entire category is essentially being rebuilt from scratch. Looker was built on server-side rendering because browser compute was not powerful enough in 2012. That architecture is the wrong starting point for 2026, when WebAssembly and DuckDB make browser-native analytics competitive with cloud queries for typical SaaS datasets. Jeff Heer's Mosaic framework is not a startup's attempt to invent browser-native analytics: it is the output of years of academic research at one of the world's best data visualisation labs, built on top of D3.js and Vega, which are themselves Heer's prior inventions used by researchers and engineers at every major technology company. The angel roster is the market validation signal that matters most: Mark Nelson served as CEO of Tableau and CTO of Concur, where he personally experienced the exact problem Ridge is solving from the buyer's perspective. Chris Stolte co-founded Tableau and served as CTO. Adrien Treuille founded Streamlit. Carlos Guestrin co-founded Turi (acquired by Apple) and runs Stanford's AI Lab. These are the people who built the analytics infrastructure Ridge is now superseding. When they write personal cheques into a new analytics company, it is because they believe the architecture is genuinely better, not just iteratively improved.

Investors: Madrona (lead, Tim Porter + Mark Nelson, former Tableau CEO), TheFounderVC, Angels: Chris Stolte (Tableau co-founder + CTO), Adrien Treuille (Streamlit founder), Carlos Guestrin (Stanford AI Lab co-founder), Elissa Fink (former Tableau CMO), Jeff Hammerbacher (Cloudera founder), and other Tableau/Trifacta/Streamlit alumni

Open roles at RIDGE AI

3 positions we're tracking. Roles are re-checked daily and removed when filled.

Software Engineer (Browser-Native Analytics / AI Stack)

Seattle·Mid-level

First seen 4 months ago

Apply →

Data Scientist / Visualisation Recommender Systems

Seattle·Mid-level

First seen 4 months ago

Apply →

GTM / First Commercial Hire

Seattle·Mid-level

First seen 4 months ago

Apply →
Live · tracking RIDGE AILast checked August 17, 2026

Know when RIDGE AI is hiring before anyone else

A role stays uncontested for about four days. Here's the window — and where we put you in it.

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Watching RIDGE AI

0 applicants

Role spotted & verified

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You get the alert

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You've applied

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Hits the job boards

250+

Hiring outlook

Very High. Press release explicitly names "data scientists and engineers" as the expansion focus. Four-person team with closed beta just opened and weekly customer onboarding cohorts.

Hiring intensity: 8/8

Working at RIDGE AI

Since , RIDGE AI has built AI-native embedded analytics for B2B SaaS, browser-native dashboards and conversational AI data agents deployable in hours, not months. The team is now <50 people. For a AI company this size, the reality is broad remit, direct access to founders, and equity that still means something if the company works out.

The majority of roles are in Seattle.

How to actually get hired at RIDGE AI

Why applying the normal way doesn't work

At <50 people, RIDGE AI has no recruiting team. Your application lands with a founder who is also running sales, product and payroll. The obstacle isn't a queue or an ATS, it's being seen at all. Cold outreach outperforms the form here, consistently.

Who to contact at RIDGE AI

Who decides:a founder or department head
Best channel:LinkedIn or direct email

Founding team

EF
Ellie Fields
Co-Founder and CEO

Ellie is one of the most credentialed product leaders in Seattle's technology ecosystem, and her specific combination of experience is what makes her the right founder for Ridge at this moment. She holds a BS in Engineering and a BA in Policy from Rice University, followed by an MBA from Stanford's Graduate School of Business. Her career began with a short stint at Microsoft before she joined Tableau Software, where she stayed for twelve years and rose to Senior Vice President of Product Development. Those twelve years span the entire formative arc of Tableau's growth: she was part of the core team that conceived, built, and launched both Tableau Public (the free community product that drove viral adoption) and Tableau Online (the cloud-hosted SaaS offering that drove enterprise subscription revenue). Her nickname within Tableau is "the Godmother of Tableau Public," which captures something important about her product instincts: she built the community product that made Tableau the default data visualisation vocabulary for an entire generation of analysts. She led product strategy and engineering across mobile apps, collaboration, search, and content experience during the period when Tableau went from a fast-growing startup to a Salesforce acquisition at $15.7 billion. She then became Chief Product and Engineering Officer at Salesloft, leading engineering for a sales workflow platform where she directly experienced the problem Ridge is solving: "I routinely experienced the problem where our team was creating real value for customers and had no good way to prove it. We would spend months building dashboards instead of focusing on what made us different." That quote, from the Ridge press release, is not a founder crafting a narrative. It is a CPO who spent months of her own team's engineering capacity building analytics dashboards that should have taken hours. Ridge is the product she wished she had at Salesloft. She is active on LinkedIn and has written thoughtfully about the transition from large company executive to early-stage founder.

JH
Jeff Heer
Co-Founder and Chief Scientist

Jeff Heer is, without overstating it, one of the most consequential computer scientists in the history of data visualisation. His academic pedigree is from UC Berkeley, where he completed his BS, MS, and PhD in Computer Science, and his career has spanned both pure research and applied commercial work in a way that is unusually rare. As a graduate student at Berkeley, he developed Prefuse and Flare, two of the first widely-used visualisation frameworks. He then joined Stanford's CS faculty as an assistant professor from 2009 to 2013, where he worked with Mike Bostock on the Protovis and D3.js visualisation systems. D3.js is now the foundation of almost every interactive data visualisation on the web. He moved to the University of Washington, where he co-directs the Interactive Data Lab and has continued a research programme that produced Vega, Vega-Lite, and most recently Mosaic, the open-source framework that Ridge's entire platform is built on. Mosaic is architecturally significant: it is an academic research output that enables highly interactive, browser-native analytics using DuckDB and WebAssembly, and it is now a production commercial product at Ridge. His research has received essentially every major award in the HCI and visualisation field: MIT Technology Review's TR35, an Alfred P. Sloan Fellowship, the ACM Grace Murray Hopper Award, the IEEE Visualization Technical Achievement Award, and induction into both the IEEE Visualization and ACM CHI academies. He was named an ACM Fellow in the 2024 class "for contributions to information visualization, human-centered data science, and interactive machine learning." His citation count on Google Scholar is 39,699, he is cited by researchers at Google, Microsoft, Adobe, and essentially every major technology company that builds data products. He co-founded Trifacta in 2012 with Joe Hellerstein and Sean Kandel, which built interactive data transformation tools and was acquired by Alteryx in 2022. His student list on his faculty page is itself a who's who of the data industry: Mike Bostock (D3.js, then New York Times, then Observable), Ravi Parikh (Heap, then Airplane, then Airtable), Dominik Moritz (now CMU faculty), Arvind Satyanarayan (now MIT faculty). When Jeff Heer founds a company, the research that powers it has been proven over decades in both academic and commercial settings. Ridge is not a bet on whether the technology works. The technology already works. The bet is whether it can be packaged and distributed at commercial scale.

What to show them

Ridge's platform is architecturally unusual: it runs analytical queries inside the browser using DuckDB and WebAssembly rather than on a server. Building features on top of this architecture, extending the Mosaic framework, and integrating the AI data agent layer requires someone comfortable working at the intersection of JavaScript/TypeScript frontend, embedded database systems, and LLM integration. The founding engineering team comes from Tableau and AppOmni, which means the culture values rigorous product engineering over hacking. Core skills: TypeScript/JavaScript, WebAssembly or DuckDB experience (strong plus), data visualisation libraries (D3.js, Vega, or Mosaic directly), LLM API integration, frontend performance engineering, embedded systems or in-browser database experience. Proof of work: Fork the Mosaic open-source framework (github.com/uwdata/mosaic), build a small interactive dashboard on top of it that renders a meaningful dataset, and add a minimal natural language query layer that translates a plain English question into a SQL query against the DuckDB instance. Share the repo. It is the exact technical stack Ridge is building on, and shipping something with it shows you have already done the orientation that takes most candidates a week.

A cold email that works at RIDGE AI

Subject: Software Engineer (Browser-Native Analytics / AI Stack), [your one-line proof]
Hi Ellie, I forked the Mosaic framework and built a small dashboard on top of it with a minimal NL-to-SQL layer, as a way to understand the browser-native architecture problem before reaching out. There were a few DuckDB edge cases I ran into around query cancellation that I thought were interesting. Happy to share the repo and the write-up.

What RIDGE AI screens for

Four people, closed beta with weekly customer cohorts, a pre-seed led by the most credentialed analytics investor roster imaginable, and a press release that specifically names "data scientists and engineers" as the expansion focus. The founding team is technically exceptional but small: Ellie Fields on product and CEO, Jeff Heer as chief scientist, Andy Caley as founding engineer (ex-Tableau), and Fritz Lekschas as founding research engineer (Harvard PhD, 20+ visualisation publications). The next hires are likely a second or third software engineer who can work on the browser-native rendering stack and AI data agent layer, a data scientist who can improve the recommendation systems for dashboard generation, and eventually a commercial hire as beta converts to paid accounts.

A tailored CV beats a generic one. Use RIDGE AI's job description language to clear filters.

Mistakes that kill RIDGE AI applications

A recycled CV gets rejected fast at RIDGE AI (<50 people). They notice.

Skip 'I'm looking for...' — start with The embedded analytics market has a technical debt problem so large that the entire category is essentially being rebuilt from scratch and your specific angle on solving it.

The wait-and-hope strategy fails. Follow up on day five — response rates roughly double.

Live · tracking RIDGE AI

Applying to RIDGE AI? Get the contact, not the form.

The RIDGE AI interview process

3 stages · 7 days typical · take-home: yes · modelled from similar companies

We don't yet have verified candidate reports for RIDGE AI. What follows is the typical process for a <50-person AI company — treat it as a model, not confirmed detail.

Interview stages

1

Intro Call

Video call · 30 min

What it tests:

Culture fit and role expectations

Usually run by:

Founder or hiring manager

2

Technical Deep Dive

Video call or in-person · 60 min

What it tests:

Past projects and problem-solving approach

Usually run by:

Technical founder or lead

3

Final Round

In-person or video · 45 min

What it tests:

Team fit and offer discussion

Usually run by:

Founding team

RIDGE AI take-home assignment

RIDGE AI 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.

RIDGE AI interview timeline

Expect days total. Compared to similar AI companies (10 days median), RIDGE AI is faster.

Interviewed at RIDGE AI?

Tell us how it went — stages, questions, timeline. Takes 90 seconds and it's how this page stays accurate for the next person.

Submit your RIDGE AI interview experience →

RIDGE AI jobs, frequently asked questions

How many jobs does RIDGE AI have open?

As of April 2026, RIDGE AI has 3 open positions.

Does RIDGE AI hire remotely?

No remote roles right now — all positions are in Seattle.

What roles is RIDGE AI hiring for?

RIDGE AI is hiring across Engineering, Design, Other. The most recent opening is Software Engineer (Browser-Native Analytics / AI Stack).

How do I apply for a job at RIDGE AI?

Apply via the links above. For tips, read our guide on how to get hired at RIDGE AI.

Does RIDGE AI respond to cold emails?

Not enough data yet on RIDGE AI's cold email response rates.

Who is the hiring manager at RIDGE AI?

At this size, hiring is usually run by a founder or department head.

How competitive is it to get hired at RIDGE AI?

Typical applicant count for AI roles (<50 people): 50-100 in two weeks. Apply fast.

How many rounds is the RIDGE AI interview?

3 stages: Intro Call, Technical Deep Dive, Final Round.

Is the RIDGE AI interview hard?

Expect technical depth and system design, not algorithm trivia. Candidates report Technical Interview as the toughest stage.

Does RIDGE AI give a take-home task?

Yes, RIDGE AI includes a take-home assignment.

How long does RIDGE AI take to get back to you?

Around 7 days across the full process.

What should I prepare for the RIDGE AI interview?

technical depth and system design is the priority. Show you can work autonomously — that matters more than algorithms at <50 people.

Where is RIDGE AI based?

RIDGE AI is headquartered in Seattle, US.

Live · tracking RIDGE AILast checked August 17, 2026

Get RIDGE AI roles before they're posted

A role stays uncontested for about four days. Here's the window — and where we put you in it.

Notify me when RIDGE AI hires

From $9/month, cancel any time.

live+2h+4hday 3day 7+

Watching RIDGE AI

0 applicants

Role spotted & verified

1

You get the alert

1

You've applied

~8

Hits the job boards

250+

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