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SciFin

A context layer that reconciles what your systems say with what's actually happening

4 open rolesSeed · $44M50+ peopleSan Francisco, USA

Last verified September 2, 2026 · Updated daily

What SciFin is building

SciFin is built around one idea Mohit Aron calls context convergence: pull the information scattered across finance, accounts, deals, forecasts, reps, territories, customer conversations and operations into one place, and then keep continuously reconciling it against reality rather than letting it drift. His framing of the problem is the sharpest line in the launch: "We need to move from systems of record to systems of reality." The headline on the site is "Close the Context Gap," and the gap is literal. A CRM tells you a deal is at 70%. The call transcript says the champion left. The invoicing system says they downgraded last quarter. Three systems, three truths, and no layer that adjudicates between them. SciFin ingests across CRM, call notes, documents and email and maintains a curated body of business knowledge that specialist agents work against — tracking metrics, surfacing deal risk, flagging churn signals, updating reports. The surface is an AI companion called Pixie, named after Aron's dog, reachable through web, voice, email, Slack and WhatsApp. That range of entry points is a deliberate bet: the people who need reconciled context are reps and revenue leaders who live in messaging apps, not in another dashboard tab. The initial focus is go-to-market and revenue, where Aron argues the value is highest in midmarket and enterprise because that is where operational complexity makes an information gap expensive. The architecture is not GTM-specific though, and "initial focus" is doing visible work in every piece of the launch messaging.

Why this matters

This is the third company from a founder who has already built two that reached over a billion dollars in ARR. Aron wrote code on Google File System, was founding CTO at Nutanix, then founded and ran Cohesity. He is credited as a father of hyperconvergence, which is the same structural move he is making again: take a capability that has been smeared across many disconnected systems and converge it into one substrate. The timing argument is straightforward and Altimeter's Apoorv Agrawal states it plainly: "Trusted context will make enterprises truly rely on AI." Every enterprise AI deployment in 2026 is bottlenecked on retrieval quality, and retrieval quality is bottlenecked on whether the underlying context is correct. Most of the money in the last two years went into agents that reason well over data nobody has reconciled. SciFin is a bet that the reconciliation layer, not the reasoning layer, is where the durable enterprise value sits. A $44M seed against that thesis is investors pricing in the founder's track record of being right about infrastructure convergence twice.

Investors: Altimeter (Apoorv Agrawal) and Madrona — co-leads, Foundation Capital, S32, Zetta Ventures

Open roles at SciFin

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

Founding Backend Engineer (distributed context store and reconciliation)

San Francisco, USA·Mid-level

First seen today

Apply →

Applied AI Engineer (specialist agents behind Pixie)

San Francisco, USA·Mid-level

First seen today

Apply →

Integrations Engineer (CRM, telephony, email, Slack, WhatsApp surfaces)

San Francisco, USA·Mid-level

First seen today

Apply →

Enterprise Account Executive (midmarket and enterprise revenue teams)

San Francisco, USA·Mid-level

First seen today

Apply →
Live · tracking SciFinLast checked September 2, 2026

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Watching SciFin

0 applicants

Role spotted & verified

1

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~8

Hits the job boards

250+

Hiring outlook

Aron has said the company plans to build out its teams and expand platform capabilities alongside the raise, and SciFin is going live at Dreamforce this year, which forces a GTM buildout on a fixed date. No public careers page or live postings yet, so the intent is clear but the roles are not published. Score reflects strong implied hiring rather than confirmed open reqs.

Hiring intensity: 6/8

Working at SciFin

Founded in 2024, SciFin is A context layer that reconciles what your systems say with what's actually happening. They're now people. For a AI company this size, the reality is opportunity to shape your role based on the company stage.

The majority of roles are in San Francisco, USA.

How to actually get hired at SciFin

Why applying the normal way doesn't work

SciFin runs an applicant tracking system, but hiring managers still work referrals first. A cold application to SciFin isn't dead, it's just fourth in line behind internal referrals, sourced candidates and recruiter pipelines.

Who to contact at SciFin

Who decides:the hiring manager
Best channel:LinkedIn or direct email

What to show them

Build a small reconciliation engine over two deliberately disagreeing sources — say a CRM export and a set of call transcripts. Do not just merge them. Detect the conflict, assign confidence, decide which source wins under which conditions, and expose the provenance of every resolved field. Write up how you handled the case where both sources are stale. That is the actual hard problem in context convergence and it is a distributed-systems consistency problem, which is the vocabulary Mohit thinks in.

A cold email that works at SciFin

Subject: Founding Backend Engineer (distributed context store and reconciliation), [your one-line proof]
Hi Mohit, "systems of record to systems of reality" is the reconciliation problem, so I built a small version: two conflicting sources, per-field provenance, confidence-weighted resolution. The interesting failure was <the specific case where both sources were wrong and the engine had to abstain>. Coming from GFS and Cohesity you've solved consistency at a much harder scale — I'd like to work on it at SciFin.

What SciFin screens for

Altimeter and Madrona co-leading is the tell. Madrona has a long relationship with Aron and published a full conversation with him on founding and scaling companies, so this is a repeat-founder bet from people who have watched him work. Altimeter's Agrawal is investing in the trusted-context thesis explicitly. A $44M seed and a founding team drawn from Google, Meta, Microsoft, Amazon, Netflix and Adobe means the technical bar is set at senior-infrastructure level from day one, and there is no scrappy early-engineer window here. The candidate edge is narrow and specific: SciFin has picked go-to-market as the wedge but built a general context substrate, so the people who join now while the first vertical is being shaped get to influence what generalises. Dreamforce in this cycle is the forcing function; being in conversation before that is materially different from being in conversation after.

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

Don't make these mistakes

Do not pitch Mohit on AI. He has been building distributed storage since Google File System and has taken two companies past $1B ARR; a note about how transformative LLMs are will read as someone who looked up the funding and nothing else. Equally, do not treat SciFin as a CRM competitor or a better dashboard — the entire thesis is that dashboards are the symptom. What earns a reply is a specific, concrete instance of context divergence you have personally lived: two systems that disagreed, what the disagreement cost, and why no amount of retrieval over either one would have caught it. Speak in the language of reconciliation and correctness, which is the language of the distributed-systems career he actually had.

Mistakes that kill SciFin applications

A recycled CV gets rejected fast at SciFin ( people). They notice.

Skip 'I'm looking for...' — start with This is the third company from a founder who has already built two that reached over a billion dollars in ARR and your specific angle on solving it.

Applying and waiting = silence. Follow up at day five — it roughly doubles your odds of a reply.

Live · tracking SciFin

Applying to SciFin? Get the contact, not the form.

The SciFin interview process

4 stages · 14 days typical · take-home: yes · modelled from similar companies

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

Interview stages

1

Recruiter Screen

Phone or video · 30 min

What it tests:

Basic qualification and logistics

Usually run by:

Recruiter or HR

2

Hiring Manager Interview

Video call · 45 min

What it tests:

Role fit and experience deep-dive

Usually run by:

Hiring manager

3

Technical/Functional Round

Video call · 60 min

What it tests:

Skills assessment and problem-solving

Usually run by:

Team members

4

Final Round

In-person or video · 60 min

What it tests:

Culture fit and cross-functional alignment

Usually run by:

Senior leadership

SciFin take-home assignment

SciFin 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.

SciFin interview timeline

Expect days total. Compared to similar AI companies (14 days median), SciFin is about average.

Interviewed at SciFin?

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 SciFin interview experience →

SciFin jobs, frequently asked questions

How many jobs does SciFin have open?

As of September 2026, SciFin has 4 open positions.

Does SciFin hire remotely?

No remote roles right now — all positions are in San Francisco, USA.

What roles is SciFin hiring for?

SciFin is hiring across Engineering, Marketing. The most recent opening is Founding Backend Engineer (distributed context store and reconciliation).

How do I apply for a job at SciFin?

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

Does SciFin respond to cold emails?

Response rate data for SciFin not yet confirmed.

Who is the hiring manager at SciFin?

At this size, hiring is usually run by the hiring manager.

How competitive is it to get hired at SciFin?

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 SciFin interview?

4 stages: Recruiter Screen, Hiring Manager Interview, Technical/Functional Round, Final Round.

Is the SciFin interview hard?

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

Does SciFin give a take-home task?

Yes, SciFin includes a take-home assignment.

How long does SciFin take to get back to you?

Around 14 days across the full process.

What should I prepare for the SciFin interview?

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

Where is SciFin based?

SciFin is headquartered in San Francisco, USA.

Live · tracking SciFinLast checked September 2, 2026

Get SciFin 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 SciFin hires

From $9/month, cancel any time.

live+2h+4hday 3day 7+

Watching SciFin

0 applicants

Role spotted & verified

1

You get the alert

1

You've applied

~8

Hits the job boards

250+

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