Temper — Founding Engineer

Type: Full-time | On-site | San Francisco, CA (5 days/week) Compensation: $150K–$300K + 0.4–0.8% equity Hiring count: 1 Visa sponsorship: No new H-1B sponsorship. Open to transfers (OPT, H-1B transfer, O-1, TN); case-by-case for exceptional candidates. Reports to: Heinrich Brunhöber, Co-founder (hiring manager) — no LinkedIn URL in source

About Temper

Temper is building an AI-native integration platform for the physical economy — specialized AI agents that automate the full lifecycle of system integrations (requirements, code generation, testing, deployment, and production upkeep) across manufacturing, warehousing, trucking, and logistics. The pitch is an AI-native replacement for the system-integrator consulting industry (Infosys/Cognizant/Accenture-style work). It has paying enterprise customers, including multi-billion-dollar logistics companies, with integrations running in production today.

Founded: 2023 | Team size: 5 | Total funding: $8.3M Industry: AI, B2B, Devtools, Enterprise, Logistics, Manufacturing Website: www.ontemper.com Office: Jackson Square, San Francisco, CA

Why Candidates Should Join

• First engineering hire: Own core systems end-to-end and set the engineering patterns for every future hire.
• Real traction: Paying enterprise customers with production integrations and more demand than the team can currently handle.
• Experienced founders: The founding team previously scaled a leading eCom logistics startup from pre-seed to 400+ people.
• Build at the frontier: Purpose-built AI coding agents plus a "mini-Vercel" integrations runtime — work spans the agentic side and the heavy-infra side of the product.

Intake Call Summary

• Agentic integration platform (IPaaS) for supply chain / real-economy verticals; automating connectivity between companies and replacing outdated systems.
• Founding engineer spanning the agentic side and the infrastructure side; full-stack with a backend focus; TypeScript required.
• Must-have: VC-backed startup experience (seed–Series B). Exposure to AI agents required; building agents from scratch is a strong plus.
• Team: CTO, CPO, and two freelance engineers; the hire works mainly with the CTO and CPO.
• Comp $150K–$300K depending on experience; onsite 5 days/week in SF.
• Urgency: wants to fill in 2–3 months, but will wait for the right person.
• Pain point: 80+ interviews with no hire; needs someone who can build from scratch and handle product complexity.
• Interview includes a systems-design case study and a live problem-solving session; ideally a ~2-day paid work trial.
• Sponsorship possible for stellar candidates but not preferred (friction).

The Role

Founding engineer building purpose-specific AI coding agents and the infrastructure runtime that hosts and runs integrations — owning core systems end-to-end.

What You'll Be Doing

• Build and design new, purpose-specific AI coding agents from scratch for supply-chain connectivity.
• Develop and maintain the core infrastructure for hosting and running integrations (effectively a mini-Vercel for the platform).
• Own core systems end-to-end, from the agent platform to the integrations runtime, making foundational architectural decisions.
• Establish the engineering patterns and practices that shape the future team and product.
• Work across both the cutting-edge agentic side and the complex, heavy infrastructure side of the product.

Tech stack: TypeScript, React, Bun, Effect-TS, PostgreSQL, Kubernetes, AWS

Qualifications

Seniority

• 2–5 years of experience as a full-stack or backend engineer [Required]

Work Experience

• VC-backed startup experience (seed to Series B) [Must have]
• Shipped and owned complex software products end-to-end, with at least one tenure at a standout startup [Required]
• Former founder, or founding/early engineer who built 01 at a fast-growing, high-caliber startup [Strongly preferred]

Education

• Undergrad in CS or engineering (flexible when work pedigree is strong) [Required]
• Top-50 technical school or clear academic spike: tradeable against startup pedigree [Strongly preferred]

Hard Skills

• Proficient in TypeScript and modern full-stack product development [Must have]
• Agent-native: hands-on building with AI agents/LLMs using current, cutting-edge patterns [Required]
• High-agency side projects (agentic tools, launched products) that show craft and initiative [Strongly preferred]

Soft Skills

• High degree of autonomy and ability to build from scratch [Must have]

Traits to Avoid

• Requires significant direction or structured tasks to be productive
• Career exclusively at big tech, enterprise, or non-tech companies
• Outside the experience band: internship-only / under ~2 years, or 8+ years / management-only focus

Role Details

• Salary | $150K–$300K |
• Equity | 0.4–0.8% |
• On-site policy | In-office in San Francisco, CA, 5 days/week |
• Visa sponsorship | No new H-1B; transfers (OPT, H-1B transfer, O-1, TN) fine; case-by-case for exceptional candidates |
• Employment type | Full-time |
• Location | San Francisco, CA |

Screening Questions

1. Can you be on-site in SF? If not, are you willing to relocate?
2. What is your salary expectation?
3. How actively are you exploring new opportunities?

Interview Process

Stage 1 — Submit candidate After submitting, you'll be notified if the hiring manager wants to proceed.

Stage 2 — Intro Screen (20 mins)

Stage 3 — Deep Dive (45 mins)

Stage 4 — Technical Systems Design Intake notes a systems-design case study and a live problem-solving session; a ~2-day paid work trial is the ideal.

Stage 5 — On-site

Stage 6 — Offer Extended

Stage 7 — Candidate Hired

Ideal Companies & Backgrounds

Updated Apr 4, 2026

Target companies Vercel

Note: only Vercel was captured — the company list appears collapsed in the copied HTML (a "Copy companies" control was present with no expanded list). Expand the full list before the next sourcing pass.

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

Thomas C. — LinkedIn Building / "Vibing" | San Francisco

• Strong company pedigree
• Built 01
• Strong school

Rohan Taneja — LinkedIn AI @ Vercel | UC Berkeley M.E.T. alum | prev SWE @ Chime, DoorList | San Francisco

• Dev-tools company (Vercel is super ideal)
• Strong 01 experience

David Dalmaso — LinkedIn Member of Technical Staff @ Perplexity | San Francisco

• Very strong companies
• Seed-to-Series-B startup experience
• Strong school

Bryce Huang — LinkedIn Software Engineer @ Anyscale | San Francisco

• Strong seed-to-Series-B experience
• Strong school

Rejected Candidate Feedback

Standing feedback

• Prioritize candidates with 2–5 years full-time experience at a VC-backed startup (seed–Series B) — internships or big-tech-only paths must be ruled out.
• Focus on those who demonstrate end-to-end, founding-engineer / 01 experience in full-stack/backend roles using TypeScript and modern AI agent frameworks.
• Screen for clear motivation and on-site SF availability, with willingness to embrace an intense, high-autonomy startup environment (no new H-1B sponsorship).
• Ensure candidates exhibit deep technical excellence and concrete production results, not just side projects or academic prototypes.

HM recalibration — Aug 18, 2026 (newest bar; supersedes where in tension)

• Headcount is now 1 (they hired 2 through Paraform); the bar is higher and precision matters more than volume.
• Hard must-have: 2–5 years full-time as a full-stack/backend engineer at a VC-backed startup (seed–Series B), with at least one "stellar" startup on the resume. Internship-only, new-grad, or big-tech-only profiles are rejected regardless of school.
• Ideals: former founders or founding/early engineers who built 01; agent-native engineers using the latest AI/LLM patterns; high-agency side projects; strong TypeScript.
• Trade-offs OK: top-50 school is no longer a hard filter. Strong startup pedigree can fully substitute for school pedigree (and vice versa).
• Screen before submitting: clear motivation for an intense seed-stage environment, strong communication, SF onsite 5 days/week, and no new H-1B sponsorship (transfers/O-1/TN fine). Each of these has killed multiple candidates at interview stage.