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/version management in production * Fine\-tuning, model serving, or inference optimization experience * Background scaling systems from zero to first real users **How to apply** Email your CV to hiring@graxe.ai. No degree, no problem — show us what you’ve built instead. Tell us what you’ve made with AI, share a portfolio or GitHub, and tell us why equity\-only founding work at the frontier of AI–human interaction is the right move for you right now. Show us something you shipped where AI was the core, not Pay: $1\.00 \- $131,109\.86 per year Work Location: Remote