Backend Engineer AI Agent Infrastructure

Backend Engineer

AI Agent Infrastructure

The basics

Compensation

Equity only. No cash salary at this stage. Founder-level equity with a standard vesting schedule (typically 4 years / 1-year cliff — final terms set in your offer).

Education

No degree required. We don’t care where (or whether) you went to college — only what you’ve built and how fast you learn.

Stage

Stealth-mode startup. We can’t share everything publicly yet; once we’re talking (and an NDA is in place) you’ll get the full picture.

Location

Remote-first, async-friendly, with occasional team syncs across time zones.

Mindset

Founding-team ownership. Small team, wide scope, fast decisions. We want self-motivated builders who run at hard problems and want to dominate the new world of AI–human interaction.

About the role

You’ll own the backbone that lets our AI agents actually do things: orchestration, tool-calling, memory, and the services that turn model output into reliable product behavior. This is the difference between a demo and a product.

What you’ll build

• Agent orchestration and tool-use frameworks (planning, function/tool calling, multi-step workflows)
• Retrieval and memory systems (vector stores, RAG pipelines, context management)
• Robust APIs and event-driven services that the rest of the team builds on
• Guardrails, retries, fallbacks, and observability so agents behave under real-world conditions

You should have

• Strong backend experience in Python, Go, TypeScript/Node, or similar
• Hands-on experience building AI agents and integrating LLM APIs (OpenAI, Anthropic, open models, etc.)
• Experience with agent frameworks and patterns (tool calling, ReAct-style loops, orchestration libraries) and vector databases
• Comfort designing APIs, data models, queues, and cloud infrastructure (AWS/GCP, containers)
• A bias toward shipping and measuring, then hardening

Nice to have

* Experience running LLM evals and prompt/...