Senior Full-stack AI Engineer
Toyo AI · Anywhere in the World · posted 8 months ago
What We’re Building
- Agent systems: session handling, agent communication, execution environments, and reliability.
- AI engineering practices: agents-in-the-loop for development, evaluation frameworks, and building reliable AI systems at scale.
Our architecture has two tightly integrated layers:
Edge-native control plane:
Real-time APIs and session management run at the edge using durable, stateful primitives. We use Durable Objects for session registries, message streaming, live voice calls, and messaging bridges (SMS, WhatsApp, Slack). Long-running workflows survive failures, with a relational database behind a connection proxy for core data.
Secure agent VMs:
Each organization runs agents inside isolated virtual machines with full filesystem access, browser automation, and persistent state. Sessions connect via ACP (JSON-RPC over WebSocket). VM lifecycle management, snapshots, boot environments, and OS-level reliability are core parts of this role.
Application layer:
TypeScript across the stack. APIs built with Hono and end-to-end type safety. React 19 on the frontend. Enterprise SSO for authentication and provider-agnostic model routing so models can be swapped without changing agent logic.
What You’ll Work On
- Agent reliability: Designing human-in-the-loop checkpoints, approval workflows, and structured validation to prevent costly mistakes.
- Session infrastructure: Building resilient session lifecycles, multi-agent orchestration, and recovery after timeouts or failures.
- Secure VM environments: Hardening boot processes, snapshots, isolation, and OS-level recovery mechanisms.
- AI-native development: Defining how agents help build Toyo itself—issue triage, automated feedback loops, and evaluation pipelines.
- Event-driven agents: Scheduled agents, webhook-triggered workflows, and messaging integrations that keep working even when no one is online.
You’ve fundamentally changed how you work with AI—not just adopted tools. You understand what works in production versus demos and experiment with new techniques as they emerge. Formal education matters less than what you’ve actually built.
Strong signals:
- Claude Code is your primary development environment
- You’ve shipped real-world agent systems
- Hands-on experience with LLM APIs, prompts, tools, structured outputs, and evaluations
- Deep understanding of edge-native, stateful distributed systems
- Experience working with VMs or containers and debugging OS-level failures
- Strong TypeScript skills and attention to correctness
Nice to have:
- Experience with agent protocols (ACP, MCP, etc.)
- WebSocket-heavy real-time systems
- Thoughtful approaches to agent security and credential isolation
Not a fit if:
- You require rigid specs and mature codebases to get started
- You view AI as a minor productivity boost rather than a fundamental shift in how software is built
What You Get
- Compensation: CAD $200K–$325K salary + equity
- Ownership: Direct influence on product and architecture from day one
- Culture: A small team that uses the same AI-first workflows we build
- Remote-first: No HQ, no commute, no bureaucracy
- Team retreat: Annual in-person offsite (last year: Sevilla)
Email [email protected] with the subject: Senior AI Engineer
Skip the cover letter. Send something you’ve built—a repo, write-up, or live project. Tell us what you find hardest about building reliable agent systems and how you’d approach it.
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