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 such as LangChain, LangGraph, and DSPy.
• Evaluate AI system performance using 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, provide implementation plans, and own features throughout the software development lifecycle.
• Identify risks, dependencies, and data limitations early and propose workable solutions.
• Challenge unclear requirements and contribute pragmatic, value-driven alternatives.
• Stay current with developments in LLMs, RAG, prompt optimization, model evaluation, fine-tuning, and applied AI frameworks, assessing their 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 or applied data science experience, including hands-on work with AI, NLP, machine learning, deep learning, or language-model-based applications.
• Strong Python skills and experience building clean, maintainable, production-ready software.
• Hands-on experience with GenAI or LLM-based solutions or open-source models.
• Solid understanding of software engineering practices, including testing, CI/CD, and version control.
• Experience with model evaluation, monitoring, or experiment tracking tools such as MLflow.
• 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 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 and a comprehensive benefits package.
• Training and development programs and access to an e-learning platform.
• An onboarding program supported by a dedicated Buddy.
• Participation in an annual, company-wide integration event.
• A work environment based on Scandinavian organizational culture.
• Growth opportunities through an internal program.

Benefits

• Sports activity cost sharing.
• Private medical care.
• Foreign language class cost sharing.
• Professional training and course cost sharing.
• Life insurance.
• Integration events.
• Corporate gym and corporate sports team.
• Coffee / tea.
• Employee parking and bicycle parking.
• Extra social benefits, holiday funds, and Christmas gifts.
• Employee referral program and charity initiatives.
• Modern, ergonomic office and yoga in the office.