Call for Engineer

Hermes Web: Call for Founding Engineer Hermes Web is looking for a founding engineer to build the first polished, hosted personal AI agent product. Some facts about us: Incubated by Open Core Ventures, the studio founded by Sid Sijbrandij (ex-CEO of GitLab) Building the hosted, non‑technical‑user version of Hermes Agent — the fastest‑growing open‑source agent framework after OpenClaw OCV underwrites infrastructure and LLM costs, so you optimize for growth and polish, not unit economics Fully remote, product‑focused, compressed sprint cadence If you want to own product and engineering end‑to‑end, ship consumer‑grade polish in a space that's still raw, and help define what a mainstream AI agent product looks like, this is for you. Requirements High agency, ship fast without hand‑holding Strong Python skills — FastAPI or similar production web framework experience required Strong frontend skills (React, Next.js, TypeScript) for the chat, memory, and activity surfaces Experience with auth, billing, and multi‑tenancy in production products Container orchestration experience (Kubernetes, Nomad, ECS, or equivalent) Experience with AI‑native tools (Cursor, Claude Code, model APIs) Knowledge of agents, LLM gateways, rate limiting, and abuse prevention Comfortable working across frontend, backend, infrastructure, and AI workflows The kind of person we want: someone who has shipped a consumer or prosumer product they're still proud of, and who responds to an aggressive timeline with "tight but doable if we cut X, Y, Z" rather than "let me spec it first." Experience with agent frameworks (Hermes, OpenClaw, LangGraph) LLM gateway or proxy work Stripe subscription billing at scale Production experience hardening agentically‑generated code OSS contributions Consumer AI product experience (Cowork, Cursor, or similar) Project: Hosted Hermes Agent Platform 1. Introduction We are building a multi‑tenant hosted platform that gives anyone their own personal Hermes agent running in the cloud in under 60 seconds. No terminal, no API keys, no configuration. The agent persists, remembers them, and gets better over time. This project includes: Per‑user Hermes containers with network and storage isolation A warm pool provisioning system for instant signup‑to‑first‑message A production‑hardened chat, memory, and activity interface An LLM gateway that meters usage, enforces caps, and prevents abuse Bundled Claude Sonnet access — users never see an API key or model selector Stripe billing infrastructure and self‑serve subscription flows 2. Requirements Platform and provisioning Per‑tenant container orchestration via Kubernetes or Nomad Warm pool pattern for sub‑90‑second provisioning Idle sleep and fast wake (under 2 seconds on incoming message) Persistent per‑tenant memory and conversation storage Auth via Clerk or Auth0 (email + Google OAuth, email verification required) Frontend React, Next.js, TypeScript, Tailwind, shadcn Multi‑tenant chat, memory, and activity surfaces Graceful handling of connection loss, agent timeouts, container restarts Streaming responses, conversation history, new‑thread flows LLM gateway Proxy every Anthropic API call from every tenant container Hold Anthropic API keys server‑side; tenant containers never see them Per‑tenant metering with second‑by‑second granularity Hard daily and monthly cost caps Circuit breakers for runaway loops Ops kill switch for any tenant Billing and ops Stripe subscription integration at $20/mo Self‑serve upgrade, downgrade, cancel Internal ops dashboard for user management and anomaly response Runbooks for common failure modes 3. Non‑Goals Developer‑facing platform Self‑hosted desktop or mobile apps Skills marketplace or plugin ecosystem Workflow builder, triggers, scheduled agents Multiple LLM providers or model selection Bring‑your‑own API key Forking Hermes — we track upstream and contribute back 4. Prior Art Hermes Agent — the open‑source framework we build the hosted experience on top of OpenClaw — the largest agent framework today and reference for community patterns and growth dynamics LangGraph Deep Agents — architecture patterns for stateful long‑running agent workflows Anthropic MCP — server design patterns for tool interfaces and permission‑aware context Cowork (Anthropic) — polish bar and UX patterns for non‑technical AI agent products Cursor agent UI — interaction model for AI agents in consumer products #J-18808-Ljbffr Open Core Ventures