Home › Companies › Lavendo › Solutions Engineer, Data Infrastructure (SF)
Solutions Engineer, Data Infrastructure (SF)
Lavendo · San Francisco · Hybrid · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Lavendo |
| Title | Solutions Engineer, Data Infrastructure (SF) |
| Normalized title | - |
| Department / team | Solutions, Sales Engineering & Pre‑Sales / Solutions, Sales Engineering & Pre‑Sales |
| Location | San Francisco, CA, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-06-01 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Lavendo. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Solutions, Sales Engineering & Pre‑Sales. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Lavendo |
| Source | e071dcd1-0b25-4d58-ac1d-36b223b36110 |
| ATS provider | Ashby |
Description
Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.
About the Company Our client is a YC-backed AI startup solving one of enterprise data's most stubborn problems: getting accurate, structured information out of complex documents at scale. Their breakthrough platform combines intelligent schema mapping with fine-tuned extraction models — doing what legacy OCR and traditional parsing tools consistently fail to do. They're processing over 1 billion pages for Fortune 50 companies and top global private equity firms, backed by Sequoia Scout, Y Combinator, Daniel Gross, and Nat Friedman.
The Mission To become the document intelligence layer that the world's most sophisticated enterprises run on — where every complex, unstructured document becomes reliable, structured data.
The Opportunity This isn't a support role dressed up as Solutions Engineering. You'll be the technical anchor of every enterprise deal — owning discovery, demos, pilots, and production deployments end-to-end, working shoulder-to-shoulder with AEs and directly alongside the founders. At a 33-person company with real enterprise traction, your fingerprints will be on every major customer win.
Tech stack: Python, Kubernetes, APIs, Distributed Systems, AWS, GCP, Azure, Docker, Helm, Terraform
What You'll Do Own all technical touchpoints in the sales cycle — discovery, demos, proof-of-concept evaluations, and production rollouts
Deploy and configure extraction pipelines inside customer environments, from pilots through to enterprise-scale production
Diagnose and resolve accuracy, latency, and infrastructure issues across distributed systems — be the person customers trust when things get hard
Build Python tooling and customer-facing utilities to support integrations and downstream workflows
Sit at the intersection of customer, ML, platform, and product — funnel real signal back into the roadmap
What You Bring 3–7 years in a customer-facing technical role — Solutions Engineer, Forward Deployed Engineer, or Implementation Engineer at a technical SaaS company (not a simple SaaS; your customers had real infrastructure questions)
Early-stage startup experience (Seed–Series B); Big Tech background considered only if paired with genuine startup and B2B-focused experience
Solid grip on sales methodology — MEDDIC, Command of the Message, or equivalent; you know how deals get stuck and how to unstick them
Hands-on with APIs, distributed systems, and production infrastructure; Kubernetes experience is a strong plus
Proficient in Python — you write tools, not just read them
Background in data infrastructure, ML platforms, or document processing is a meaningful plus
Must not require visa sponsorship — the company cannot sponsor at this stage
Key Success Drivers You're technical and customer-obsessed — you can go deep on infrastructure in one conversation and then translate it into business value in the next
You run toward ambiguity — early-stage means the playbook isn't written yet; you're comfortable writing it
You stay in the customer lane — your career shows consistent commitment to customer-facing roles; pivots to pure engineering signal the wrong fit
You have a builder's instinct — deploying pipelines and writing integration code feels natural, not foreign
You care about what you're selling — document intelligence, computer vision, NLP, and data infrastructure genuinely excite you
Why Join? Tier-1 conviction from day one: Backed by Sequoia Scout, Y Combinator, Daniel Gross, and Nat Friedman — the investor syndicate that bets on category winners
This is a proven platform, not a bet: Already processing 1B+ pages for Fortune 50 enterprises and leading global PE firms; real revenue, real customers, real scale
Small team, real ownership: 33 people means direct founder access and outsized impact — you're not a ticket in a queue
Compensation that reflects the role: $125K–$155K base, OTE $180K–$220K, competitive equity, and performance bonus
Full benefits: Medical, vision, and dental; daily meal stipend; relocation assistance for Bay Area moves
Interviewing Process HR Screen
Interview with Hiring Manager
Technical Interview with CTO
Take-Home Exercise
Offer
We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.
Full job record
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| Board ID | e071dcd1-0b25-4d58-ac1d-36b223b36110 |
| Provider | ashby |
| Provider Job Key | eea3d598-53e6-432c-b4ee-d8df5cecb6f5 |
| Title | Solutions Engineer, Data Infrastructure (SF) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Solutions, Sales Engineering & Pre‑Sales |
| Team | Solutions, Sales Engineering & Pre‑Sales |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/lavendo/eea3d598-53e6-432c-b4ee-d8df5cecb6f5 |
| Apply URL | https://jobs.ashbyhq.com/lavendo/eea3d598-53e6-432c-b4ee-d8df5cecb6f5/application |
| First Seen At | 2026-05-29 07:09:17Z |
| Last Seen At | 2026-06-06 09:36:40Z |
| Last Checked At | 2026-06-06 09:36:40Z |
| Last Changed At | 2026-06-01 13:20:43Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=lavendo/date=2026-06-06/2026-06-06T09-36-21-050Z-f1bc386ab7ca1e5e52bfcb8fb1d911966f186ec972e2d6a344d2acade9db2a0f.json |
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