You've been watching the AI capability curve. You've done the mental math. You know where this is going.
While most people are still debating whether LLMs can "really" reason, you're thinking about what happens when agents replace entire functions, when systems can debug themselves, when software can operate without humans touching it.
We're building that future. Right now. With real companies.
Rocketable acquires profitable SaaS companies and transforms them into fully autonomous systems. No human operators. No engineering team shipping features. No support staff answering tickets. Just AI running the entire business.
This sounds crazy to most people, but the trajectory is obvious if you're paying attention. Within a few years, the question won't be "can AI run a software company?" It will be "why would a human?"
If you think we're wrong, don't apply. If you think we're early, let's talk.
You'll be the architect of the platform that makes this possible.
- Starting point: A live SaaS company. Revenue. Customers. All the messy reality of a business that currently requires humans to operate.
- Week 4: Your agent swarm handles first-line customer support. A meta-layer analyzes every human intervention not just logging it, but learning from it. Why did a human need to step in? How do we eliminate that trigger?
- Week 12: Hours of autonomous operation. Agents creating specialized sub-agents. The system building its own tools when it hits capability gaps. Performance metrics tracking toward superhuman baselines.
- Beyond: Each new acquisition stress-tests your abstractions. Different tech stacks. Different domains. Different edge cases. The platform either generalizes or we start over and rebuild until it does.
Apply if:
- You believe full automation for software companies isn't just possible, it's inevitable (and you want to be the one building it).
- You'd rather fail at something unprecedented than succeed at something incremental.
- You want to work on the hardest version of the problem, not the safe version that gets you acqui-hired in 18 months.
Don't apply if:
- You think "human in the loop" is a permanent design pattern, not a temporary constraint.
- You're uncomfortable with the societal implications of what we're building. We think about them. We just don't let them paralyze us.
- You're optimizing for a good story for your next job, not for a decade of building something durable.
This isn't a research role. You need to ship production systems.
- Systems (5+ years): You've scaled production systems to 100K+ DAU. You understand distributed architectures deeply (microservices, event-driven systems, message queues). Full-stack fluency from frontend to infrastructure. TypeScript and Python preferred.
- AI/ML: Hands-on LLM integration (OpenAI, Anthropic, Google). You treat prompt and context engineering as an engineering discipline with version control, evals, and systematic optimization. You've built systems to measure AI performance. Bonus points for self-improving systems, RL, RLHF.
- Infrastructure: Kubernetes. Docker with real security understanding. Infrastructure as Code. Cloud platforms (GCP or AWS preferred). CI/CD that doesn't suck. Observability that helps you debug distributed systems. Security fundamentals.
- Founder: Alan Wells. Ex-Cruise, ex-Uber ATG. 10+ years of experience building AI/ML products that sense, predict, and act in mission-critical applications.
- Funding: $6.5M seed from Y Combinator, True Ventures, Bloomberg Beta, Indie.vc, and others. Capital for 3+ acquisitions.
- Team philosophy: Small by design. In-person 5 days/week (San Francisco default, Marin County possible).
Rocketable is a bet that AI capabilities will continue accelerating. That autonomous systems will outperform human-operated ones. That the companies who figure this out first will have a compounding advantage.
We might be wrong. But if we're right, you'll have built the infrastructure that runs a new kind of company. This is the highest-leverage engineering work that exists right now.
That's the trade. Interested? Apply here.