LakeFusion

Why applying the normal way doesn't work

At this size (<50 people), LakeFusion has no recruiting function. Founders handle hiring alongside everything else. Reach them directly or get lost in the inbox.

Who to contact at LakeFusion

Who decides

a founder or department head

Best channel

LinkedIn or direct email

What to show them

The Full Stack roles build the LakeFusion UI and platform surface: the interfaces through which data stewards configure entity resolution rules, review golden records, manage survivorship logic, and trigger syncs. This is not a consumer product. The users are data engineers and MDM administrators. The UI needs to be functional, fast, and deeply integrated with the platform's API surface. The AI/ML Engineer role builds and improves the entity resolution and deduplication models that sit at the heart of the product: LLM-based matching, vector embeddings for record similarity, and the classical ML approaches that handle high-volume deduplication cost-effectively.

A cold email that works at LakeFusion

What LakeFusion screens for

Silverton Partners leads this round and is the most important signal. They are an Austin-based venture firm with a concentrated portfolio of enterprise and B2B software companies. They back companies with genuine technical differentiation and push hard on enterprise GTM. Their portfolio includes companies across data infrastructure, SaaS, and developer tools. When Silverton leads an enterprise data infrastructure seed, they are expecting aggressive customer expansion in healthcare, financial services, and manufacturing, the three sectors LakeFusion has named explicitly. That is a commercial hiring mandate alongside the engineering one. Carbide Ventures, the existing investor from the November 2025 round, re-upped. That is the clearest possible internal signal: the investors closest to the company's day-to-day progress chose to put in more money. Carbide focuses on AI, data, and enterprise infrastructure. Their GP Pankaj Tibrewal noted that AI is not just driving demand for MDM, it is transforming how MDM itself gets done. That framing shapes the hiring bar: LakeFusion needs engineers who understand both the AI layer (entity resolution, LLM-based matching) and the data infrastructure layer (Databricks, Delta Lake, lakehouse architecture). The operational signal is equally important. Vikas posted publicly about completing five LakeFusion deployments in four days. That is not a press release claim. That is a live team executing at speed with a real customer queue. A team of 25 completing five enterprise MDM deployments in four days is running at a pace that requires more people immediately.

Tailor your CV to the specific LakeFusion role rather than sending a general one. Applications that mirror the language of the job description clear automated filters at a materially higher rate.

Mistakes that kill LakeFusion applications

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

• ✕

  Lead with their problem, not your ambition. LakeFusion is focused on Enterprise AI is stalling not because models are bad but because the data underneath them is broken — 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.

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

Interview stages

1. 1

   Intro Call

   Video call · 30 min

   What it testsCulture fit and role expectations
   Usually run byFounder or hiring manager
2. 2

   Technical Deep Dive

   Video call or in-person · 60 min

   What it testsPast projects and problem-solving approach
   Usually run byTechnical founder or lead
3. 3

   Final Round

   In-person or video · 45 min

   What it testsTeam fit and offer discussion
   Usually run byFounding team