AGI INC

AI Engineer - Backend

San Francisco Office

Sponsorship not specifiedDetected 350 days ago

iOSAndroidGitPostgreSQLRESTLLMsAgentic AIResearchCollaboration

About the role

Trustworthy, consumer-grade agents that redefine human-AI collaboration for millions.
We're a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind.
Make them feel like magic, not infrastructure.

Responsibilities

Forward-deployed engineers, by giving them backends partners can integrate against without a six-week meeting
How to design backends for LLM-powered systems where latency, cost, and non-determinism are first-class concerns
On-device / cloud co-design - when to push compute to the phone and when to keep it on our side

Company info

Build everyday AGI.
Software shouldn't wait for commands; it should partner with you, amplifying what you can do every single day.
WHY AGI, INC.
We're industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.
Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.
We are supported by tier-1 investors who funded the first generation of AI giants; now they're backing us to build the next: everyday AGI. (Watch the demo https://drive.google.com/file/d/1ZydjdMeMh3x-QItUPQFbJUbhBW-4-XHa/view?usp=sharing)
If you see possibility where others see limits, read on.
Build the systems our agents run on.
Our agents are only as trustworthy as the backend behind them.
Every API call, every retry, every queued job is the difference between an agent that feels alive and one that feels like a chatbot.
You'll own the systems that turn research into product - model orchestration, agent state, partner integrations, the data plane - and you'll make them fast enough, observable enough, and boring enough that the rest of the team can ship without thinking about them.
This is for the backend engineer who has been the on-call hero before, who has strong opinions about queues and idempotency, and who wants to design infrastructure for a product where the floor is "millions of devices."
🤩 TASKS YOU WILL OWN
The agent backend end-to-end - model orchestration, tool-use plumbing, agent state, retries, observability
The data plane behind every agent action - Postgres schema, caching, queues, event streams - at OEM scale
Production SLAs, on-call, and the reliability bar for everything the agent touches in the cloud
🤚 AREAS WHERE YOU WILL ASSIST
Research, by shipping their work to real users in days, not quarters - and feeding back what breaks in production
iOS and Android, by drawing the right line between on-device and cloud so neither side carries the wrong weight
📚 SKILLS YOU'LL BE EXPECTED TO TEACH
How to run a production system you'd happily put your name on - observability, incident response, capacity planning
🧑‍🎓 SKILLS YOU'LL BE EXPECTED TO LEARN
The internals of agentic systems from the people who published the canonical papers on them
What it takes to run agent infrastructure at OEM scale, across Samsung, OPPO, Lenovo, and Vertu devices

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