Software Engineer, AI & Data Systems | San Francisco (On-site) | Up to $280k Base + Equity

"I know kung fu."

Neo needed a headjack and a loading program. You just need strong backend fundamentals and the nerve to operate millions of autonomous AI agents in production.

The company (identity classified, which is ironic)

Our client is one of the fastest-growing data infrastructure startups in San Francisco, and what they are building sounds like science fiction until you see the revenue chart. They deploy tens of millions of autonomous AI agents across the open web to construct a living identity graph spanning billions of individuals and hundreds of millions of businesses: the contextual backbone for the next generation of AI applications.

The irony of us anonymising a company whose entire product is knowing exactly who everyone is? Not lost on us. "You are being watched" was a warning in Person of Interest. Here, it's the pitch deck.

They are backed by two of the most respected names in early-stage venture, have hit multi-million ARR with 13x revenue growth since their seed round earlier this year, and have just been accepted into one of Silicon Valley's most selective founder residencies (think Jedi Academy, but with worse sleep schedules and better GPUs). The team is eight people. Eight. Doing this. That's the whole point.

The mission

This is a genuine high-ownership role, not a "high ownership" role that turns out to mean fixing other people's tickets. You take ambiguous customer problems, choose the architecture, ship the product, and own it in production. "Do. Or do not. There is no try" applies here more literally than at most companies, because on an eight-person team there is nobody behind you.

You will:

• Build and ship customer-facing products and core platform capabilities across backend, data, infrastructure, and frontend surfaces
• Design and operate high-volume data pipelines and services at genuinely massive scale, with real reliability, security, and observability requirements
• Build AI agents, agent harnesses, and developer tools, then keep them running when they're loose across 250 million websites
• Make architecture decisions, explain your trade-offs like an adult, and iterate as assumptions change
• Work directly with the founders and customers, turning vague requests into clear product decisions and working software

The engineering culture is unapologetically AI-native. They expect you to use modern AI tools aggressively while keeping strong engineering judgment and full accountability. The replicants don't run the show; you do. But you'd be mad not to use them.

Who they're looking for

1 to 6 years of experience in backend or data engineering, building high-volume pipelines and AI systems. In practice, that means:

• Strong backend coding: APIs, data models, distributed systems
• Experience building and operating high-volume data pipelines
• AI-native development habits: LLMs, agent frameworks, and the instincts for when to trust them
• You have owned a production system end-to-end, from concept through deployment and operations
• Time at a talent-dense early-stage startup (seed to Series B), shipping across product and infrastructure
• Bonus points for having built agents, pipelines, or identity and matching systems at scale
• A CS degree from a strong school

A word of warning: if your resume says "contributed to" more than "built and ran," this is not the role. They have politely rejected candidates whose experience was feature work rather than full-system ownership. "Never tell me the odds" is optional; owning the outcome is not.

The deal

• Salary: up to $280K base
• Equity: competitive, in a company growing at a rate that makes the equity conversation genuinely interesting
• Location: San Francisco, five days a week in office. No, not hybrid. Not "flexible." This is the on-site one, and the pace is the reason why
• Visa: open to visa transfers (OPT, H1B transfers welcome)
• Timing matters: they are hiring one engineer, and the start date needs to work by mid-September to align with the residency programme. Doc Brown had a lightning strike to hit. You have a calendar

Why this role, why now

Eight people. Multi-million ARR. 13x growth in a matter of months. A residency programme that takes ten companies per cohort. This is the moment in the movie right before things get big, and joining now means real ownership of real products at a company where a single engineer visibly moves the graph.

Roy Batty had seen things you people wouldn't believe. Attack ships on fire off the shoulder of Orion. You'll see things too: mostly Grafana dashboards at 2am while your agents crawl a quarter of a billion websites, but honestly, that's cooler.

How to apply

Send your resume through or reach out for a confidential chat. The interview process is refreshingly short at two steps, and this team moves faster on strong candidates than almost anyone else we work with.

"There is no spoon." There is, however, a desk in San Francisco with your name on it. Take the red pill.