AI Engineer (M/F/D)
Key responsibilities
Independently deliver scoped AI, GenAI, NLP, and RAG features of moderate complexity
Develop and enhance RAG pipelines, including document parsing and ingestion, chunking and metadata strategies, query transformation, retrieval and ranking, response generation and grounding
Build GenAI features using LLM APIs, structured prompting, and orchestration frameworks (e.g., LangChain, LangGraph, DSPy, etc.)
Evaluate AI system performance using practical methods such as retrieval metrics, response quality assessment, hallucination analysis, latency measurement, cost analysis, and failure-case testing
Understand engineering trade-offs across model quality, latency, cost, reliability, maintainability, and implementation complexity
Own features end-to-end - from clarification and experimentation to deployment and initial support
Translate requirements into user stories and provide implementation plans, as well as own features end-to-end throughout the software development lifecycle - from clarification and experimentation to deployment and initial support
Identify risks, dependencies, and data limitations early and propose workable solutions
Challenge unclear requirements and contribute with pragmatic, value-driven alternatives
Stay close to new developments in LLMs, RAG, prompt optimization, model evaluation, fine-tuning, and applied AI frameworks, and assess where they create real business impact
To succeed and thrive in the role, you bring:
A degree in Computer Science, Software Engineering, AI, Machine Learning, or similar- or equivalent professional experience
3+ years of professional AI engineering/applied data science experience, including hands-on experience with AI, NLP, machine learning, deep learning, or language-model-based applications
Strong Python skills and experience building clean, maintainable, and production-ready software
Hands-on experience with GenAI or LLM-based solutions or open-source models
Solid understanding of software engineering practices (testing, CI/CD, version control, etc.)
Experience with model evaluation, monitoring, or experiment tracking tools (i.e., MLflow or similar).
Ability to work in cross-functional, agile teams and communicate clearly in English
Nice to have:
Experience with cloud platforms such as Google Cloud or similar
Familiarity with RAG architectures, embeddings, vector databases, and retrieval techniques
Exposure to fine-tuning or model optimization approaches
Experience with Kedro for building modular, reproducible data and ML pipelines, and KServe for scalable, production-grade model deployment and inference on Kubernetes
Knowledge of agentic workflows, tool-calling systems, agentic search, MCP, or A2A integration patterns
What we offer :
Employment based on an employment contract, along with a comprehensive benefits package
Training and development programs, as well as access to an e-learning platform
Onboarding program with the support of a dedicated Buddy
Participation in an annual, company-wide integration event
A work environment based on Scandinavian organizational culture
Opportunities for growth through our internal program
Benefits:
Sharing the costs of sports activities
Private medical care
Sharing the costs of foreign language classes
Sharing the costs of professional training & courses
Life insurance
Integration events
Corporate gym
Corporate sports team
Coffee / tea
Parking space for employees
Extra social benefits
Holiday funds
Christmas gifts
Employee referral program
Charity initiatives
Bicycle parking
Modern and ergonomic office
Yoga in the office