AI Automation Engineering
Role details
Job location
Tech stack
Job description
As our first dedicated AI Automation Engineer, you will be a foundational part of our data team's expansion. You will join a core team of 3 Data Engineers, and will be one of two new dedicated roles (alongside an Analytics Engineer) being added to build out our advanced data capabilities. You will be pivotal to GitGuardian's growth and success by establishing and leading our internal AI and automation function, acting as a force multiplier for the entire company.
You will design, build, and deploy an internal AI platform-automations, agents, and data-driven workflows-that other teams adopt and extend. You'll sit at the crossroads of Business Process, AI Application, and Data, directly improving how GitGuardian operates at scale.
Your main responsibilities will be to:
- Design and Build Business Automations: Identify, design, and implement robust workflows connecting systems (HubSpot, Notion, Linear) to eliminate manual processes using n8n or Python.
- Build Internal Apps & Agents: Develop Dust-powered agents and wrap them in lightweight interfaces (simple UIs, CLIs, or chat) for self-serve usage and strong adoption.
- Fuel with Data: Partner with Analytics and Data Engineers to leverage trusted models and pipelines-ensuring quality, observability, and fast iteration.
- Strategic Partner: Proactively map processes, spot high-impact opportunities, and translate needs into scalable, user-friendly solutions.
- Centre of Excellence: Set paved paths, best practices, and manage our AI & Automation tooling (Dust, n8n) to enable teams to ship safely and fast.
- Own the Lifecycle: Discovery to production, documentation, enablement, monitoring, and iterative improvement focused on reliability, UX, and adoption.
- Stay at the Forefront: Bring pragmatic innovation from agentic workflows, retrieval, and evaluation into production-not just experiments.
Technical Environment
- Core Languages: Python, SQL
- AI: Dust, LangChain
- Automation: n8n
- Data Warehouse: Snowflake
- Orchestration & Deployment: Dagster, Kubernetes, Docker, Terraform
- Data Ingestion: Fivetran, Airbyte, custom scripts
- Data Sources: PostgreSQL, Elasticsearch, various APIs (Hubspot, Notion, etc.), To know more about yourself, your professional experiences and your motivations. Also to assess end-to-end delivery of automations/agents; stakeholder communication; pragmatic tool choice (no/low-code vs. Python); familiarity with Dust/LLM platforms.
- Technical interview
To evaluate your skills for the position and project yourself into the role. We will assess practical automation engineering, AI agent design, and data integration.
4.1 Final interview with an Executive Manager
To detail our company's vision and ambitions for the next couple of years. We will assess your product mindset, change management, and enablement of non-technical users.
Requirements
Do you have experience in Terraform?, * 5+ years in a technical or solutions role (Analytics Engineering, Solutions Engineering, Data Analysis, or technical Business Ops) with a track record of production automations or tools.
- Python expert for APIs, data manipulation, and robust scripts/apps.
- Hands-on with Generative AI (Dust, RAG, agentic workflows, prompt engineering).
- Pragmatic: use no/low-code (n8n/Zapier/Make) when fastest; drop to Python when it matters.
- Product mindset for internal tooling: intuitive interfaces, clear UX, adoption across non-technical teams.
- Strong stakeholder management and communication; collaborate across technical and non-technical teams.
- Familiar with data warehousing (Snowflake) and SQL to fuel automations.
The following skills would strengthen your application but aren't required:
- Previous experience in a high-growth B2B SaaS company.
- Experience building lightweight internal UIs or CLIs to package automations/AI agents (e.g., simple web apps or chat interfaces).
- Experience with our specific Data stack (Dagster, Fivetran/Airbyte, Metabase).
- Familiarity with containerization and orchestration (Docker, Kubernetes).
Benefits & conditions
- Package that includes stock-options
- Lunch voucher (Swile)
- Non-charged health insurance for children (Sidecare / Generali)
- Up to €300 to improve your home office set-up
- Yearly holiday allowance
- Referral bonus of 4000€ for any new Guardian we might hire thanks to you
- Team building: monthly budget dedicated to each employee that you can spend as you wish, with colleagues (latest examples to date: Michelin star restaurant, karaoke, stand-up show, kitesurfing week-end, ...)
And also...
- Remote policy: hybrid (2 days/week at the office)
- Opportunities for career development in the long term