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Tech Stack
Tools & technologiesDockerJavaScriptKubernetesMySQLNext.jsNode.jsNumpyPandasPostgresPythonPyTorchReactScikit-LearnSQLTensorflowTypeScript
About the role
Key responsibilities & impact- Develop and maintain our full‑stack applications within a modern JavaScript/TypeScript ecosystem
- Design and implement scalable backend services with Node.js and Nest.js
- Implement high‑performance frontend solutions using React.js and Next.js
- Design and optimize relational databases (PostgreSQL, MySQL, MS SQL)
- Containerize and orchestrate services using Docker and Kubernetes
- Develop and integrate REST APIs
- Build and operate data pipelines, feature stores and ML workflows for our agentic systems
- Develop, train and evaluate machine learning models for marketing use cases (attribution, targeting, forecasting, anomaly detection)
- Implement retrieval‑augmented generation (RAG) pipelines (embeddings, vector stores, re‑ranking)
- Set up and maintain LLM evaluation frameworks, prompt optimization and systematic quality benchmarks
- Apply code harnesses (notably Claude Code and Codex) in the daily development process — from planning through implementation to code review
- Collaborate closely with the founding team on the product architecture of agentic systems
Requirements
What you’ll need- Several years of professional experience in full‑stack development
- Strong knowledge of TypeScript and JavaScript
- Confident with React.js, Next.js, Node.js and Nest.js
- Experience with relational databases (PostgreSQL, MySQL, MS SQL)
- Practical experience with container technologies (Docker, Kubernetes)
- Familiarity with REST API design and Git workflows
- Solid Python skills including the common data/ML stack (pandas, NumPy, scikit‑learn, PyTorch or TensorFlow)
- Experience across the end‑to‑end ML model lifecycle: data preparation, feature engineering, training, validation, deployment, monitoring
- Understanding of statistical fundamentals (hypothesis testing, regression, classification, time series)
- Experience with modern LLM workflows: prompt engineering, RAG, embeddings, vector databases (e.g., Pinecone, Weaviate, pgvector)
- Practical experience in model evaluation: metrics, benchmarks, A/B testing, systematic evaluation frameworks
- Familiarity with MLOps tools (e.g., MLflow, Weights & Biases, DVC) is a plus
- Experience with Claude Code and/or Codex is highly welcome — otherwise a clear willingness to actively learn them
- Excellent German (C2) and English skills (at least C1)
- Genuine interest in generative AI and agentic systems
- Builder mentality: you deliver production software, not just prototypes
- Analytical mindset: you make data‑driven decisions and can critically assess model behavior
- Preferably experience developing custom agents, sub‑agents or specialized coding workflows (e.g., Custom Commands)
- Experience with MCP (Model Context Protocol) and tool‑calling architectures
- Familiarity with agent frameworks (Mastra, LangGraph, Vercel AI SDK)
- Experience with fine‑tuning, LoRA adapters or distillation
- Background in marketing analytics, attribution models or performance marketing data
- Publications, Kaggle achievements or open‑source contributions in the ML/AI space
- Background in B2B SaaS or enterprise software
Benefits
Comp & perks- Competitive salary and equity program (ESOP)
- Fully funded access to all relevant code harnesses, LLM APIs and developer tools (Claude Max, Codex, GitHub Copilot, etc.)
- Compute budget for experiments, model training and ML workloads
- Modern hardware setup (MacBook Pro of your choice)
- Flexible working hours and remote options
- Office in Berlin and a location in Dubai (DIFC AI Campus)
- Steep learning curve in agentic AI, LLM orchestration and AI‑native engineering
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
JavaScriptTypeScriptReact.jsNext.jsNode.jsNest.jsPostgreSQLMySQLMS SQLPython
Soft Skills
analytical mindsetbuilder mentalitydata-driven decision makingcollaborationcommunication