About the role
Member of Technical Staff: Agent Runtime (Ego) Location: San Francisco, CA (hybrid) · Reports to: Founding team
About the role
Ego AI is a YC-backed applied AI research lab building the behavioral infrastructure for AI companions and agents. We work at the intersection of real-time conversational instincts, memory, and persistent identity; the layer that makes AI feel genuinely alive. We're a small, fast-moving team and we're defining a new category of human-AI interaction.
What you'll do
Own the agent harness. Design and maintain our core agentic loop (plan → tool call → observe → repeat → finalize) as a small, legible state machine. Errors are first-class: malformed tool calls, hallucinated tool names, and throwing tools get fed back to the model. They never crash the loop.
Make execution durable. Build checkpointed, resumable sessions backed by a database: step logs with pending/committed status, idempotency keys on side-effecting tools, and a clear account of the at-least-once vs exactly-once boundary. A crash between the LLM call and the tool call, or mid-compaction, must never corrupt a session or double-fire a POST.
Solve long-horizon context. Own our compaction strategy: pinned goals, running summaries, sliding windows of recent turns, and retrieval over older state. A 30+-step task should finish aimed at the original goal, within budget.
Design for extensibility. Ship a tool registry (name + JSON schema + handler) that teammates and partners can extend without touching the loop. Validate schemas before handlers run. Keep model adapters swappable in one place.
Ship deployable systems. Deliver one-command local bring-up, persistence behind an interface (Postgres ↔ SQLite ↔ Cloudflare storage), clean HTTP APIs, and secrets hygiene. Build per-user durable agent instances that wake on triggers (cron, webhooks, inbound events). Cloudflare Durable Objects experience is a real plus.
