Founding Software Engineer (ArborAI)

Note: Candidates must be authorized to work in the United States. Arbor AI is not able to provide employment visa sponsorship at this time.

Arbor AI is VC-backed and building AI-native monetization infrastructure for the open internet—so ads and commerce can be faster, smarter, and measurable in real time across websites, apps, and agentic surfaces.

As a Founding AI-Accelerated Software Engineer (Backend, Infrastructure & Measurement) (one of the first ~10 employees), you’ll help design and ship the low-latency systems and measurement stack that directly power performance and revenue. This is “AI-accelerated” in the real way: you’ll use AI tools to move faster, but you’ll still rely on systems thinking, engineering judgment, and tight iteration to deliver reliable outcomes in a fast-moving environment.

Also a fit if you call yourself: Backend Engineer, Infrastructure Engineer, Systems Engineer

You’ll build and operate the core backend systems that make monetization work at scale, including:

• Low-latency serving and decisioning: backend systems for ad serving, ranking, and auctions where milliseconds matter and correctness can’t slip
• Delivery infrastructure for campaigns: targeting, pacing, campaign management, and delivery plumbing that stays reliable under real traffic
• Experimentation measurement: A/B testing, attribution, and incrementality systems that help teams trust what they’re seeing
• Performance engineering: improve latency, reliability, throughput, and system behavior as usage grows and requirements evolve
• Large-scale data pipelines: signals, reporting, and analytics pipelines that turn raw events into usable measurement
• Full-stack when it helps: build internal tools and platform surfaces when needed to unblock the system end-to-end
• Founders close by: work directly with the founders on architecture and product direction—your decisions shape what we build next
  

• Strong computer science fundamentals and the engineering judgment to turn ambiguity into working systems
• Proven backend distributed systems experience building production services end-to-end
• Production engineering skills: you can design, debug, and operate systems—not just write code
• Experience optimizing performance in latency-sensitive or high-throughput environments
• A hands-on, ownership mindset: you take problems from “not working” to “working reliably”
• AI tools used in practice: you can use AI to accelerate iteration while maintaining quality, correctness, and good engineering judgment
  

• Experience with ads/monetization/marketplaces (serving, auctions, targeting, measurement, attribution)
• Experience with large-scale data systems (streaming, batch, reporting pipelines)
• You’ve used AI tools as part of your day-to-day workflow to move faster without sacrificing quality
  

• You’ve worked where you were expected to figure things out and ship, not wait for perfect specs
• You communicate like an engineer: clear tradeoffs, crisp debugging, and decisions grounded in what the system is telling you
• You enjoy building the unglamorous foundation—infrastructure, measurement, and tooling—because that’s what makes product outcomes real
• You’re comfortable operating in a fast-changing startup where good judgment matters more than rigid process
  

You’ll be part of a small founding team building from 0→1, with direct access to the people setting the technical direction. This role is based in the San Francisco Bay Area and is primarily in-office.

Compensation is $120K–$180K (plus meaningful early-stage equity). Note: The compensation range reflects our good-faith estimate of the base salary for this role. Actual compensation will be determined based on experience, skills, interview performance, and expected scope of ownership.

Benefits include:

• Health insurance
• Dental insurance
• Vision insurance
• Paid time off
• Parental leave
• Professional development support

Note: Candidates must be authorized to work in the United States. Arbor AI is not able to provide employment visa sponsorship at this time.

If you’ve built and scaled backend or distributed systems in any high-scale environment—startup, enterprise, or open source—we’d love to hear how you approached performance, reliability, and measurement.

Interested? Start with a conversation with Navii, our hiring team’s AI—it's a chance for us to learn about your systems work and what you want to build next.