GenAI Data Engineer
Who we are?
We are building a next-generation AI-native sales automation platform for B2B teams. Our goal is to change the very paradigm of how people interact with business applications.
Manual data entry becomes a thing of the past as the platform proactively connects to your communication and information channels. It seamlessly captures, structures, and transforms data into real-time, actionable awareness.
You no longer work for the tool. The tool works for you, anticipating your needs, surfacing the right context at the right moment, and guiding your next steps with intelligence and precision.
Our vision is to give teams an always-on AI-driven partner that lets them focus entirely on creating value and closing deals.
Philosophy
We value open-mindedness, rapid delivery and impact. You’re not just coding features-you shape architecture, UX, and product direction. Autonomy, accountability, and a startup builder’s mindset are essential.
Requirements
- Strong backend: Python, FastAPI, Webhooks, Docker, Kubernetes, Git, CI/CD.
- Hands-on with OpenAI-family LLMs, LangChain/LangGraph/LangSmith, prompt engineering, agentic RAG, vector stores (Azure AI Search, Pinecone, Neo4j, hFAISS).
- SQL, Pandas, Graph DBs (Neo4j), NetworkX, advanced ETL/data cleaning, Kafka/Azure EventHub.
- Proven experience building and operating retrieval-augmented generation (RAG) pipelines.
- Familiarity with graph algorithms (community detection, similarity, centrality).
- Good English (documentation, API, teamwork).
Nice to Have
- Generative UI (React).
- Multi-agent LLM frameworks.
- Big Data pipelines in cloud (Azure preferred).
- Production-grade ML, NLP engineering, graph ML.
Responsibilities
- Design, deploy, and maintain GenAI/RAG pipelines for the product
- Integrate LLM/agentic assistants into user business flows.
- Source, ingest, cleanse, and enrich external data streams.
- Build vector search, embedding stores, and manage knowledge graphs.
- Explore and implement new ML/GenAI frameworks.
- Mentor developers and encourage team knowledge-sharing.
What else is important:
- Startup drive, proactivity, independence.
- Willingness to relocate/freedom to travel in Europe; full time.
- Eagerness to integrate latest AI frameworks into real-world production.
Our Team
Agile, tight-knit product group (5–6 experts) with deep experience in SaaS, AI, graph data, and cloud delivery. We move fast, give each member autonomy, and engineer for impact- not just features.
Who takes a final decision:
The team makes the decision based on a technical interview.
Our benefits
- Startup culture: minimal bureaucracy, maximum flexibility
- Remote-first: work from anywhere
- Unlimited vacation — we value results, not hours spent
- Opportunity to grow together with an AI-first product company
- Direct impact on a breakthrough AI-native product
Recruitment process
- HR interview (VP Team) — Technical prescreen (Q&A)
- Technical interview with CTO/Data Officer (real-life case)
- Offer
Required languages
| English | C1 - Advanced |