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
• Become part of one of Europe’s fastest-growing ClimateTech start-ups.
• Supported by leading US and EU investors, we are shaping the future of the sustainable construction and real estate industry.
• Modern headquarters in the west of Berlin: conveniently located and well connected.
• Hybrid work model with flexible working hours.
• 30 vacation days plus one additional day per year, as well as time off on December 24 and 31.
• We reward referrals for our open positions through a thoughtful and appreciative referral program.
• After the probation period: up to five days of educational leave per year with a budget of €1,500.
• BVG public transport ticket.
• Membership at Urban Sports Club.
• Don’t just work with us, but help shape the change and drive decarbonization forward.