Mid-Senior AI Engineer

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Mid-Senior AI Engineer developing high-impact AI solutions at DSV. Collaborating with international teams on AI products and capabilities across the organization.

Posted 7/1/2026full-timeHedehusene • 🇩🇰 DenmarkSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI, GenAI, and NLP, with a strong focus on developing and enhancing RAG features and pipelines. Proficient in Python and experienced in model evaluation and software engineering practices, ensuring the delivery of high-quality, production-ready solutions.

Highest-signal resume keywords

AI EngineeringNLP DevelopmentPython ProgrammingModel EvaluationGenAI Solutions

ATS Keywords

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Hard Skills

AIGenAINLPMachine LearningDeep LearningSoftware EngineeringModel EvaluationDocument ParsingResponse GenerationData Ingestion

Soft Skills

Clear CommunicationProblem SolvingCollaborationAgile Teamwork

Tools & Technologies

LLM APIsLangChainLangGraphDSPyMLflow

Industry Keywords

RAGPrompt OptimizationExperiment TrackingSoftware Development LifecycleTestingCI/CDVersion Control

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

Ownership of real AI solutions used at scale in a global organisation
Collaboration with international teams across products, engineering, and operations
A dynamic environment focused on learning, improvement, and shared success
Opportunities to grow your skills and shape how AI is applied across DSV