Flexible hybrid work (3 days remote, 2 days office)
Flexible working hours (start between 7:30-10:00)
We are developing next-generation digital products that bring AI capabilities into production. Building new intelligent features from scratch to improve and automate existing processes, and implementing a data protection platform for secure data exchange and the safe integration of external AI. In this role, you will be the driving force behind the AI layer of our platform. You will implement and integrate the intelligent capabilities that make our products smart: working with large language models (LLMs), autonomous agents, RAG pipelines, ML model integration, and AI-driven processing workflows. Your work will bring AI from research into production, making it reliable, observable, and valuable for end users. You will work within a cross-functional agile team alongside backend engineers and FE product developers to iteratively design, build, and ship AI-driven features. We're looking for engineers who are passionate about applied AI, take ownership of outcomes, and care about delivering real value in short cycles.
Key Responsibilities
AI Platform Engineering
Design and build scalable backend services and APIs using Python (FastAPI) to support ML model integration, inference pipelines, and intelligent processing workflows
Implement and orchestrate LLM-based agents, RAG pipelines, and autonomous AI workflows within the platform
Integrate machine learning models into production services with a focus on reliability, latency, and observability
Work with AI/ML frameworks and tools (LangChain, LlamaIndex, Hugging Face) to build and deploy intelligent features
Data & Knowledge Systems
Work with vector databases, embedding models, and semantic search to power knowledge retrieval and intelligent data interaction
Build data pipelines that move, transform, and enrich data for AI processing across distributed systems
Develop AI-driven features for secure data exchange and privacy-preserving data sharing, including safe integration of external AI systems
Contribute to continuous integration and continuous delivery (CI/CD) practices that keep the team shipping reliably
Ownership & Collaboration
Take ownership of features end-to-end: from concept and prototyping through implementation, testing, deployment, and production monitoring
Contribute to our ontology-based platform approach for intelligent data organization and retrieval
Required Qualifications
3+ years of backend development experience with Python
Proficiency with Python web frameworks (FastAPI, Flask)
Experience with LLM integration, prompt engineering, and AI agent frameworks (LangChain or similar)
Experience building and deploying RAG (Retrieval-Augmented Generation) pipelines
Familiarity with ML model serving, inference optimization, and integration patterns
Experience with vector databases and embedding models
Experience designing and building APIs at scale
Experience with data modeling
Understanding of microservice patterns and inter-service communication
Experience with containerization (Docker) and deployment workflows
Proficiency with Git, pull request workflows, and collaborative code reviews
Strong data protection and security awareness
Excellent communication skills and comfort with cross-functional collaboration in an agile environment
Preferred Qualifications
Experience with ML/AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
Working knowledge of Java and Spring Boot
Experience with NoSQL databases (Neo4j, Elasticsearch, Redis)
Understanding of CI/CD pipelines and automated testing for AI/ML services
Knowledge of testing frameworks (pytest)
Experience with NLP, generative AI, and conversational AI applications
Familiarity with ontology-based data modeling and knowledge graphs
Familiarity with infrastructure-as-code, monitoring, and observability tools
Graduated from FER, PMF, FOI, FESB, TVZ, or similar technical institutions
