Job Openings foam — Founding Engineer

About the job foam — Founding Engineer

foam — Founding Engineer

Type: Full-time | On-site | San Francisco, CA Compensation: $250,000–$400,000 + 0.25%–2% equity Hiring count: 1 Visa sponsorship: H-1B transfers, TN (Canada and Mexico), OPT to H-1B, H-1B1 Singapore, E-3 Australia Reports to: Founders (no named hiring manager / LinkedIn provided)

About foam

foam finds and diagnoses errors, incidents, and degradations in production before users do. When something breaks, foam cuts through the noise, identifies the single root cause, and pings the responsible engineer with a fix ready to go — no prompting required. It is positioned as the first telemetry and production system designed for LLMs, giving them full visibility into and control over running software, starting with automatic error fixes.

Published benchmark: 86% root-cause accuracy, beating Cursor + MCP setups by 20+ points.

Founded: 2024 | Team size: 1–10 (Seed) | Total funding: $10M (Khosla Ventures, Max Levchin, The House Fund, South Park Commons) Industry: AI Tools / Dev Tools Website: foam.ai Office: San Francisco, CA Customers: Perplexity, GPTZero, Together AI, Braintrust, Orb Team backgrounds: xAI, Affirm, Berkeley EECS, OpenAI

Why Candidates Should Join

  • Founding-level ownership: Real influence over system design, architecture, and product direction from day one, across full-stack, infra, and support as the company grows.
  • Genuinely hard AI problems: Building multi-agent reasoning systems on real telemetry to produce correct root-cause analyses — not pipelines or fine-tuning.
  • High-signal team and backing: $10M seed, top-tier investors, and a founding team out of xAI, Affirm, Berkeley EECS, and OpenAI, with live customers already onboard.

Intake Call Summary

  • No intake call transcript or summary text was included on the role page. An Intake Video is present but not transcribed — request the transcript or notes from Contrario if a summary is needed for scoring.

The Role

foam is hiring a Founding Engineer to build the systems that deliver accurate root-cause analysis to clients. The role is not limited to full-stack, infra, or support — as the company grows, the engineer will be pulled across all of these problem areas.

What You'll Be Doing

  • Building multi-agent reasoning systems that use real telemetry to produce correct root cause analyses
  • Getting handed problems no one has ever seen and coming up with solutions, like automating error analysis
  • Setting up telemetry pipelines, improving tooling and SDKs, and building systems that reconstruct timelines across logs, traces, and deploys
  • Building automatic instrumentation that tracks code behavior, preserves async context, and improves visibility into backend operations
  • Helping build not just the systems that deliver correct RCA, but the systems that build those systems

Tech stack: TypeScript, Node.js, Next.js, Vercel, AWS; multi-agent systems, telemetry, observability, production debugging

Requirements

  • Level 3 autonomy, operates independently without being managed
  • 1+ years using AI to solve complex unstructured problems
  • Strong communication, translates complex ideas into simple clear language
  • Demonstrable evidence of edge, clearly exceptional in some way
  • Background at a high-signal dev tools or AI company
  • Based in or relocating to San Francisco

Green Flags

  • Background at xAI, Affirm (pre-2021), Cursor, Ramp, Retool (2017 to 2021), Perplexity, DataDog, Sentry, or equivalent, strongest signal of the caliber foam is looking for
  • Has used AI to solve genuinely hard, unstructured problems in production, not just fine-tuned models or run pipelines
  • Curious and always building, merely reading is not enough, they have to get hands on with whatever their curiosity unearths
  • Gritty and courageous, does not linger in their comfort zone, swims upstream to achieve goals
  • Can estimate with high confidence quickly and manage projects with notable competence
  • Has worked at the product scope, not just feature or task level, understands the full PSHE cycle

Red Flags

  • Entrepreneur in residence of any kind
  • Last role was a manager with minimal coding (different than a tech lead)
  • Anyone pushed out of FAANG in the last two years
  • Prior work that can be summed up as data pipelines
  • Background at Salesforce or similarly slow-moving enterprise companies
  • Taking orders from VC
  • Does not have demonstrable evidence of a clear edge, average engineers do not make the bar here
  • Active manager, foam needs builders not people managers
  • Consultant Background

Role Details

Salary$250,000–$400,000Equity0.25%–2%Experience5–7 yearsOn-site policyFully in-person, San FranciscoVisa sponsorshipH-1B transfers, TN (Canada and Mexico), OPT to H-1B, H-1B1 Singapore, E-3 AustraliaRelocationFully covered: flights, 2–3 weeks temporary housing near office, $10,000 misc. 24-month repayment agreement appliesEmployment typeFull-timeLocationSan Francisco, CABenefitsUnlimited PTO; 100% medical/vision/dental; pet insurance; 401k; team lunches and outings

Screening Questions

  • None provided on the role page. (Add any client-provided screening questions here before the screening call.)

Interview Process

Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Intro chat (15–20 min) with a founder — Culture fit, background, and prior experience. Stage 3 — Technical (1 hr) with Co-Founder & COO Stage 4 — Onsite (4 hr) — 3 coding questions, 1 design question. Stage 5 — Technical #2 (45 min) with Perla Stage 6 — Offer Extended Stage 7 — Candidate Hired — Candidate accepts and starts.

Ideal Companies & Backgrounds

Updated June 26, 2026 High-signal dev tools / AI — Cursor, Factory.ai, Elastic, Perplexity AI, Grafana, DataDog, Sentry, ClickHouse, Ramp, Slack, Airtable, Brex, Blend (Pre-2020), Gusto, HeyGen, HyperDx, PlanetScale, Retool (2017 to 2021), Sigma Computing, Stytch, TailScale Ideal background tiers (from body) — xAI (2023–2025), Affirm (pre-2021), Cursor, Ramp, Retool (2017–2021), Perplexity, DataDog, Sentry, PlanetScale, Grafana, ClickHouse, TailScale, Factory.ai, HeyGen, or equivalent

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

  • None provided on the role page.

Rejected Candidate Feedback

  • None provided on the role page.