AI Engineer (M/F/D)

Our requirements

• 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

Optional

• 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

Your 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

About the project

Take a 360-degree Virtual Tour of the DSV GBS Office

• https://social.dsv.com/2QS

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

Recruitment stages

• 1.
  CV Analysis
• 2.
  Telephone contact
• 3.
  1st Recruitment meeting
• 4.
  Tests (optional)
• 5.
  2nd Recruitment meeting (optional)
• 6.
  Feedback

DSV GBS