Mid-Senior AI Engineer

Jobtailor; Hedehusene; On-site; DKK 900,000 - 1,100,000; Full time

Job summary

Jobtailor in Denmark seeks an AI Engineer to independently deliver GenAI, NLP, and RAG features of moderate complexity. You will develop and enhance RAG pipelines, including document parsing, chunking, query transformation, retrieval, and grounding, and build GenAI features using LLM APIs and orchestration frameworks.

Required hands-on AI/applied data science experience, strong Python skills, and a solid software engineering background.

Qualifications

• 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

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)
• 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

Skills

Python

GenAI

NLP

AI engineering

Education

Bachelor's degree in CS

Tools

LangChain

LangGraph

DSPy

Job description

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

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