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Mid-Senior AI Engineer
Cookie InformationMid-Senior AI Engineer developing high-impact AI solutions at DSV. Collaborating with international teams on AI products and capabilities across the organization.
Tech Stack
Tools & technologiesPython
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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AIGenAINLPMachine LearningDeep LearningSoftware EngineeringModel EvaluationDocument ParsingResponse GenerationData Ingestion
Soft Skills
Clear CommunicationProblem SolvingCollaborationAgile Teamwork