Principal AI Engineer

At Gorgias, we’re building the platform that makes this real: a unified AI agent that sells, supports, and re-engages customers across the entire journey. Conversational Commerce is the future of ecommerce, and we’re leading that shift.

Our mission is to turn every interaction between a brand and its customers into a relationship: personal, seamless, and intelligent. By combining deep product expertise with the latest in AI, we’re making shopping feel more natural, human, and connected than ever before.

To win, we focus relentlessly on:

• Mentor & Level Up: Bridge the gap between traditional software engineering and AI. You’ll mentor engineers on how to apply rigorous system design to the world of LLMs and agents.

• Continuous Observability: Take ownership of the feedback loop, ensuring that production insights from our agents directly inform the next iteration of our evaluation datasets.

• 8+ Years of Engineering Excellence: You are a Staff-level engineer first. You’ve built systems that handle high scale, and you know how to architect for long-term maintainability and performance.

• Agentic Curiosity: You’ve moved beyond the "chatbot" phase and are actively experimenting with AI Agents. You understand that the challenge isn't the prompt, but the orchestration, state management, and reliability of the agent's actions.

• Systems Thinker (Non-Deterministic Mindset): You recognize that AI is probabilistic. You are excited by the challenge of building deterministic "wrappers" and Evaluation loops around models to make them safe for production.

• The "Applied" Edge: You likely come from a background in distributed systems, internal platforms, or developer tooling, and you're now applying that rigor to the AI stack.

• Beyond the Wrapper: You have serious experience moving beyond simple API calls to architecting multi-stage AI orchestrations (agents, chained workflows, or custom runtime logic).

• Orchestration Experience: Even if you aren't an AI researcher, you have experience building complex, multi-step workflows (e.g., temporal systems, state machines, or event-driven architectures) and want to apply this to Agentic loops.

• Reliability Obsession: You understand why "vibes-based" testing doesn't work. You’ve started exploring or building Eval frameworks to measure how models perform against real-world data.

• Infrastructure Mindset: You are comfortable with the "glue" that makes AI work: vector databases, semantic caching, and API integration with third-party tools.

• Strong backend experience (Python preferred)

• Experience with distributed systems and event-driven architectures

• Familiarity with tools like Kafka, Pub/Sub, or equivalent

• Experience working with LLMs (prompting, RAG, agents, evaluation workflows)

• Experience building APIs and scalable services

• Understanding of monitoring, observability, and system performance

• Recruiter phone screen

• HM Interview

• System Design Interview

• AI Case Study (take-home, ~1–2 hours)

• Technical Deep Dive of case study

• Final Leadership Interview