Senior AI-Driven ‑Stack Engineer; Remote/Berlin
UAE/Dubai
Listed on 2026-05-29
-
Software Development
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Software Engineer
Location: Berlin / Remote (DACH time zone)
Employment Type: Full-time, permanent
Start Date: Immediate
Language: Native-level English proficiency (C1-C2 level, German a bonus)
_____________________
ABOUT US
sandan AI is a Berlin-based AI-native startup serving enterprise customers across the DACH region. We are shaping what marketing looks like in an agentic economy — and building the platform on which this new generation of marketing workflows runs.
Our ambition is to build software the way software should be built in 2026: agentic, iterative, and with AI as an integral part of the engineering workflow.
HOW WE WORK
We use code harnesses such as Claude Code and Codex not as gimmicks, but as a core part of our development process. Our engineers work daily with agentic coding workflows — from architecture sketches and implementation to refactoring and testing.
People joining us either already work productively with these tools or bring the clear motivation to learn and master them quickly and deeply.
Location: Berlin / Remote (DACH time zone)
Employment Type: Full-time, permanent
Start Date: Immediate
Language: Native-level English proficiency (C1-C2 level, German a bonus)
_____________________
ABOUT US
sandan AI is a Berlin-based AI-native startup serving enterprise customers across the DACH region. We are shaping what marketing looks like in an agentic economy — and building the platform on which this new generation of marketing workflows runs.
Our ambition is to build software the way software should be built in 2026: agentic, iterative, and with AI as an integral part of the engineering workflow.
HOW WE WORK
We use code harnesses such as Claude Code and Codex not as gimmicks, but as a core part of our development process. Our engineers work daily with agentic coding workflows — from architecture sketches and implementation to refactoring and testing.
People joining us either already work productively with these tools or bring the clear motivation to learn and master them quickly and deeply.
Tasks- Develop and maintain our full-stack applications within the modern JavaScript/Type Script 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 (Postgre
SQL, 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
Core Technical Competencies (Engineering)
- Several years of professional experience in full-stack development
- Strong knowledge of Type Script and Java Script
- Confident working with React.js, Next.js, Node.js, and Nest.js
- Experience with relational databases (Postgre
SQL, MySQL, MS SQL) - Hands-on experience with container technologies (Docker, Kubernetes)
- Familiarity with REST API design and Git workflows
Data Science & Machine Learning
- Solid Python skills, including common data/ML stacks (pandas, Num Py, scikit-learn, PyTorch, or Tensor Flow)
- 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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).