Founding Engineer - LLM Infra & Platform

PAX
San Francisco, CA, United States
11 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Artificial Intelligence Caching

Job description

Every game on Pax Historia depends on our ability to send huge numbers of requests across many AI providers and get the right response back quickly, reliably, and cheaply.

We’re hiring an engineer to own that system. You’ll work on provider reliability, structured outputs, caching, routing, and monitoring. At the end of the day, you will need to:

  • Ensure that the 37+ models on our site reliably handle our 30 billion+ monthly tokens.
  • Reduce costs and latency for our 60k+ daily active users wherever possible.

You will not be in charge of model-training. We do not run model inference ourselves.

If you’re obsessed with detail, data oriented, and have a strong tendency to verify everything, then this might be a great fit for you. We don’t expect you to have done this exact job before, but we are expecting you to be a fast learner with extremely strong fundamentals.

Logistics

You’ll be our 7th team member. We work in-person in San Francisco, 5+ days/week. We are open to sponsoring visas.

Comp will include meaningful equity to reflect your responsibility as a founding engineer.

Requirements

Artificial Intelligence (AI), Caching, Cost Control, Funding, Logistics

About the company

Pax Historia is creating the future of interactive entertainment.

We’re building the platform for worldbuilders, storytellers, and game devs to create and publish any ‘what if’ they can think of. So far, most of the 25k+ user published presets on our site are historical (eg, ‘what if Rome never fell?’), but fantasy and sci fi are the fastest growing categories on the site.

We have seen over 92 million rounds played and raised a 10M+ seed round in March. We’re backed by Y Combinator (W26), Bessemer, Pace Capital, Z Fellows, and more.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:46 min

Core terminology and audiences for interpretable artificial intelligence

Karol Przystalski · LIVE

3:15 min

Reversing the caching model for artifact delivery

Thijs Feryn Thijs Feryn · World Congress 2026 Europe

5:30 min

Building components of a real-world LLM lifecycle

Maxim Salnikov Maxim Salnikov · LIVE

3:21 min

Automating complete quality assurance pipelines with artificial intelligence

Evelyn Haslinger · LIVE

2:33 min

Maintaining prompt structures for prefix caching

Douglas Reiser Douglas Reiser · Europe 2026 Virtual

3:14 min

Building a community-governed LAMP stack for open AI

Raffi Krikorian Raffi Krikorian · World Congress 2026 Europe

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