Founding AI-Accelerated Software Engineer (Backend, Infrastructure & Measurement)

Arbor AI

$120K–$180K · San Francisco Bay Area · Primarily in-office

The Role

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

The Work

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

What You’ll Need

• 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

Even Better If

• 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

Who Thrives Here

• 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

The Team + Comp & Benefits

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

Non-Traditional Backgrounds

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.

How to Apply

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.