We’re looking for a senior-level engineer to take full ownership of our data and AI systems, from ingestion and modeling to embedding pipelines and LLM-based applications. You’ll operate across domains (data infrastructure, BI, and AI), working closely with stakeholders in product, operations, and engineering.
This is a full-stack data role with a dual mandate:

• Build and scale our AI-native data platform
• Help shape and lead a growing Data & AI team as we scale

We’re early-stage, so you’ll move between strategy and code, long-term design and fast iteration. You’ll lay the groundwork not just for the system, but for the team that will own it.

AI & Application Engineering

• Architect and deploy AI-powered systems into production (e.g., FastAPI apps with RAG architecture using OpenSearch and Langfuse)
• Optimize agentic workflows, prompt & embedding pipelines, and retrieval quality through experimentation and tracing
• Extend LLM capabilities with supervised fine-tuning (SFT) for in-domain data distributions where RAG alone underperforms

Data Engineering

• Build scalable ingestion and transformation pipelines for both proprietary and external data (using Lambda, Glue, Terraform)
• Own embedding pipelines for retrieval-augmented generation systems
• Manage infrastructure-as-code for all core components (Redshift, S3, VPC, IAM, OpenSearch)

Analytics Engineering & BI

• Maintain and evolve a clean, documented data model (dbt Cloud ⇒ leverage Fusion)
• Develop and maintain BI dashboards in QuickSight and/or Metabase
• Provide ad-hoc analytical support for product, sales, and ops teams
• Build event-driven automation and reverse ETL pipelines to serve data or AI outputs back into operational systems (e.g., HubSpot)

Leadership & Collaboration

• Work closely with stakeholders across engineering, product, and operations to define the right data products and abstractions
• Lay the foundation for a high-performing Data & AI team. Help hire, mentor, and establish best practices as we grow

Must-Haves

• Strong communication and stakeholder management in both English and German (written + spoken)
• Production-level experience in Python for data and AI engineering (pipelines, APIs, orchestration)
• Solid SQL and data modeling expertise (including incremental strategies)
• Hands-on experience with a major cloud provider (AWS, GCP, or Azure)
• Terraform/IaC experience for provisioning cloud infrastructure
• Experience using at least one modern BI tool (e.g., Metabase, Power BI, Looker)

Nice-to-Haves

• Deep AWS experience (S3, Lambda, Glue, Redshift, OpenSearch)
• Hands-on experience deploying AI/LLM-based systems into production
• Experience using dbt Cloud for transformation pipelines
• Familiarity with tracing and observability (e.g., Langfuse, OpenTelemetry)
• Experience preparing datasets and running supervised fine-tuning (SFT) of LLMs
• Exposure to reverse ETL tools (e.g., Census, Hightouch) or building custom syncs to HubSpot, Slack, APIs

With a clear commitment to excellence and a creative drive, we develop innovative products and solutions. Our team spirit is the driving force that helps us tackle every challenge together. Through flat hierarchies, we create space for creative ideas and allow everyone to actively contribute to shaping our future.

Our selection process is open to all people – regardless of age, race, origin, religion, gender, sexual orientation, gender identity and/or expression, marital status, or other legally protected characteristics.

If you are inspired by our mission but do not meet every single requirement, we strongly encourage you to apply anyway. We are not looking for perfect resumes, but for individuals with strong values and the courage to help shape a sustainable future.

Find your Purpose. We look forward to receiving your application.