Staff AI Engineer, Gorgias
€131.1-144.9k
0.018% – 0.025%
The conversational AI platform for eCommerce
Open for applications
The conversational AI platform for eCommerce
501-1000 employees
Open for applications
€131.1-144.9k
0.018% – 0.025%
501-1000 employees
Company mission
To empower eCommerce brands to grow through AI-powered customer experience.
Role
Who you are
- 8+ years of experience in software engineering
- Strong backend engineering background
- Experience building and scaling production systems
- Experience working with AI systems (LLMs, agents, or similar)
- You likely come from one of the following backgrounds:
- Staff or senior software engineer who has moved into AI systems
- Engineer working on applied AI products in production
- Experience building internal platforms or developer tooling
- 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
- What We’re Looking For:
- 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
- Tech Stack & Experience:
- 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
What the job involves
- This role will focus on building and scaling the systems that support AI evaluation and iteration, helping the team move faster and more reliably
- You’ll have a chance to:
- 🤖 Work on production AI systems used by thousands of businesses
- 🧠 Define how we evaluate and improve AI performance at scale
- 🏗️ Build internal platforms and tooling used by AI and engineering teams
- 📈 Reduce manual processes and improve iteration speed on AI features
- 👥 Collaborate across AI, ML, and product teams
- 🧑🏫 Raise the engineering bar and mentor others
- What You’ll Do:
- Design and build systems for evaluating AI performance (offline and online)
- Develop workflows and tooling for prompt iteration and validation
- Improve the reliability, scalability, and observability of AI systems in production
- Work closely with ML Engineers and AI Engineers to integrate evaluation into development workflows
- Collaborate with product teams to ship AI-powered features
- Take ownership of systems end-to-end, from design to production and monitoring
- Contribute to improving engineering practices around AI development and evaluation
- Mentor engineers and help structure how the team approaches AI engineering
- 1. Architect the Evaluation "Factory"
- End-to-End Platform Ownership: Architect and lead the development of our internal evaluation platform, moving the needle from manual testing to a fully automated lifecycle (from LLM-as-a-judge creation to production monitoring)
- Accelerate Time-to-Market: Directly impact our primary KPI by designing tools and workflows that drastically reduce the time it takes to deliver a calibrated, production-ready agent
- Infrastructure Collaboration: Partner with the Orchestration team to build the robust, scalable infrastructure required to run complex evals and agentic simulations at scale
- 2. Scaling AI Expertise
- Squad Empowerment: Serve as the "AI Technical Lead" for product squads, guiding them through the complexities of agent design, failure analysis, and prompting best practices
- Decentralize Quality: Instead of being a bottleneck, you will build the "paved road" that allows product squads to become autonomous in measuring and maintaining their own agent quality
- Standard Setting: Define what "good" looks like for AI at [Company Name]. You’ll translate non-deterministic AI behavior into predictable engineering metrics that the whole organization can trust
- 3. Engineering Leadership
- 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
Application process
- 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
Our take
With the surge in online shopping, eCommerce merchants are increasingly prioritizing customer communications to enhance the overall shopping experience. This heightened emphasis puts greater pressure on support teams to promptly and accurately address customer inquiries.
Gorgias offers an all-encompassing customer support helpdesk equipped with artificial intelligence tools tailored for customer service teams. The platform allows eCommerce businesses to streamline responses to frequently asked questions through a single application. By automating these responses, support agents can allocate more time to engaging in meaningful and profitable interactions with customers, thereby potentially driving sales.
Catering to over 15,000 brands, including prominent brands like Princess Polly, Steve Madden, and Marine Layer, Gorgias faces competition from established players like Zendesk, Freshdesk, and HelpScout. Despite this, the company has experienced notable growth, expanding its presence across the US, Europe, and Australia. Along with funding that will fuel the development of its Automation Add-on feature, aimed at providing customers with instant answers to alleviate support workload.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
19% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
May 2024
$29m
SERIES C
Aug 2022
$30m
SERIES C
Total funding: $101.4m
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Alex Plugaru
(Co-Founder & CTO)Former Web Developer at Gymglish, Eau de Web, Innobyte and Liquid Studios.
Romain Lapeyre
(Co-Founder & CEO)Former Product Manager at Work4 and Business Developer at Scalr. MA in Management from HEC Paris.
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