Staff Applied AI Engineer — Auggie Platform - CANADA (Remote)

We don't just use AI. We build with it, ship with it, and think with it. We're in the top 1% of companies applying AI effectively, not just to our products, but to how we build them. With an unlimited budget for Anthropic tokens, our engineers use AI agents to write, review, and ship production code every day. We're building toward a world where humans design systems and AI builds them, and we're already further along that path than almost anyone else.

As a Staff Software Engineer, you'll be a technical leader at the center of this transformation. You'll shape platform architecture, drive AI-powered product delivery, and raise the bar for what a small, AI-augmented engineering team can accomplish. This is a role for someone who already lives in their terminal with AI, who has strong opinions about how AI changes system design, and who wants to help define what a next-generation engineering organization looks like.

Here are examples of the kinds of initiatives you'd work on today:

Multi-agent orchestration and execution. Design and build the core systems that let multiple autonomous agents collaborate, delegate, and execute complex business workflows in production — not chatbot interactions, but structured multi-step operations running across real business data.

Autonomous workflow automation. Build the automation layer that turns business processes into agent-driven workflows with structured data models, conditional logic, and human-in-the-loop review queues that keep autonomous systems safe and reliable.

Auto-generated application UIs. Architect the systems that dynamically generate functional user interfaces from agent outputs and structured data models, letting non-technical users interact with AI-powered applications without writing code.

Platform integration and MCP infrastructure. Own the integration layer connecting Auggie to internal and external systems — building MCP servers, managing agent-to-system communication, and enabling the platform to operate across tools like Slack, Notion, Salesforce, and custom data sources.

Attributes

• You already build with AI daily. You use Claude Code as a core part of your workflow, not as a novelty

  
  

• You have strong opinions, loosely held, about how AI changes software architecture, team structure, and engineering culture

  
  

• You think in systems. You connect technical decisions to customer outcomes and long-term business value

  
  

• You communicate clearly and directly. You can explain complex tradeoffs to product, design, and executive stakeholders

  
  

• You're energized by ambiguity and speed. You thrive in a fast-growing company where the roadmap evolves and ownership is real

  
  

• You like to have fun at work. We take our craft seriously, but we don't take ourselves too seriously. We celebrate wins, crack jokes, and genuinely enjoy building together

  
  
  

Skills and Experience

• 8+ years of professional software engineering experience, with meaningful time in senior or staff-level roles

  
  

• Production experience building multi-agent or agentic AI systems — not prototypes or demos, but systems running against real data with real users

  
  

• Deep familiarity with LLM integration patterns: prompt engineering, tool use / function calling, RAG pipelines, and structured output parsing

  
  

• Experience with agent orchestration frameworks, agent-to-agent communication, or autonomous workflow execution

  
  

• Strong backend engineering fundamentals: TypeScript/Node.js, event-driven architectures, and distributed systems

  
  

• Track record of owning product-oriented technical initiatives end-to-end, from system design through production

  
  

• Experience with MCP servers, LLM-based validation, or spec-driven development workflows is a strong plus

  
  

• Startup or high-growth experience preferred, but big-company background is fine if the AI systems experience is genuinely strong

  
  
  

Tech Stack

• Backend: Node/TypeScript, Python

  
  

• AI: Anthropic Claude, MCP, LangGraph

  
  

• Data: Postgres, Redis, SQS

  
  

• Infrastructure: AWS, Kubernetes, Temporal