Key skills
DockerJavaScriptKubernetesMySQLNext.jsNode.jsNumpyPandasPostgresPythonPyTorchReactScikit-LearnSQLTensorflowTypeScriptAIMachine LearningMLLLMClaudeRAGAgenticTensorFlowscikit-learnNumPyMLOpsJupyterMLflowPineconeWeaviateReact.jsPostgreSQLREST APIGitGitHubA/B TestingRemote Work
About this role
Role Overview
- Develop and maintain our full-stack applications within the modern JavaScript/TypeScript ecosystem
- Design and implement scalable backend services using Node.js and Nest.js
- Build high-performance frontend solutions with 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 workflows, and systematic quality benchmarks
- Apply code harnesses (especially Claude Code and Codex) throughout the daily development process — from planning and implementation to code review
- Collaborate closely with the founding team on the product architecture of agentic systems
Requirements
- Several years of professional experience in full-stack development
- Strong knowledge of TypeScript and JavaScript
- Confident working with React.js, Next.js, Node.js, and Nest.js
- Experience with relational databases (PostgreSQL, MySQL, MS SQL)
- Hands-on experience with container technologies (Docker, Kubernetes)
- Familiarity with REST API design and Git workflows
- Solid Python skills, including common data/ML stacks (pandas, NumPy, scikit-learn, PyTorch, or TensorFlow)
- Experience across the end-to-end lifecycle of ML models: data preparation, feature engineering, training, validation, deployment, and monitoring
- Strong 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)
- Hands-on experience in model evaluation: metrics, benchmarks, A/B testing, and systematic evaluation frameworks
- Experience with notebook-based exploration environments (Jupyter, Colab) and transitioning them into production-ready pipelines
- Familiarity with MLOps tools (e.g. MLflow, Weights & Biases, DVC) is a plus
- Experience with Claude Code and/or Codex is highly appreciated — otherwise, a strong willingness to actively learn and adopt these tools
Tech Stack
- Docker
- JavaScript
- Kubernetes
- MySQL
- Next.js
- Node.js
- Numpy
- Pandas
- Postgres
- Python
- PyTorch
- React
- Scikit-Learn
- SQL
- Tensorflow
- TypeScript
Benefits
- A defining role in an AI-native startup with a strong enterprise focus
- Competitive salary and employee stock ownership plan (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 work options
- Office in Berlin and location in Dubai (DIFC AI Campus)
- A steep learning curve in Agentic AI, LLM orchestration, and AI-native engineering