Senior AI Engineer
Role overview
We are looking for a hands-on AI Engineer to build, test, and improve AI-driven solutions for the publishing business.
This is a practical technical role. We are not looking for someone who only talks about AI strategy, builds simple no-code automations, or experiments with visual app builders. We are looking for someone who can turn ideas into working software, test things quickly, and help move useful AI solutions toward production.
The ideal candidate is technically strong, curious, independent, and comfortable working with emerging AI technologies. You should be familiar with LLMs, APIs, agentic workflows, and frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools.
You should also be comfortable using modern agentic coding tools such as Codex, Cursor, Claude Code, GitHub Copilot, or similar systems as part of your development workflow.
Responsibilities
- check_circle Build, run, and evaluate proof-of-concept and MVP initiatives, especially within automated content creation and AI-assisted publishing workflows.
- check_circle Develop practical AI solutions using LLMs, APIs, orchestration frameworks, retrieval systems, automation pipelines, and agentic workflows.
- check_circle Experiment quickly with new tools, frameworks, models, and technical approaches.
- check_circle Translate business needs into working technical solutions with a focus on reliability, speed, and measurable value.
- check_circle Take ownership of assigned technical tasks and move work forward without constant supervision.
- check_circle Identify opportunities, blockers, and next steps proactively.
- check_circle Report progress clearly to the Tech Lead / AI Tech Manager and stay aligned with agreed priorities, processes, and reporting lines.
- check_circle Work closely with QA, product, editorial, and production teams to validate model outputs and improve reliability.
- check_circle Support the handover of validated PoCs and MVPs into production-ready solutions.
- check_circle Stay current with emerging AI frameworks, LLM capabilities, coding agents, evaluation methods, and AI engineering best practices.
Basic qualifications
- Strong hands-on experience with AI/ML tools, LLMs, API integrations, and AI application development.
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools.
- Solid programming skills, preferably in Python and/or TypeScript.
- Practical understanding of prompt engineering, retrieval-augmented generation, agents, workflow automation, model evaluation, and output validation.
- Experience using agentic coding tools such as Codex, Cursor, Claude Code, GitHub Copilot, or similar tools to build real software.
- Ability to move quickly from idea to prototype while maintaining sound engineering judgment.
- Strong analytical skills and the ability to test model outputs, interpret feedback, and improve system design.
- Comfort with ambiguity, fast iteration, and unfamiliar technical problems.
- Ability to work independently while keeping managers informed and following agreed direction.
- Clear communication skills for cross-functional collaboration.
Tags & Focus Areas
About BETTER COLLECTIVE A/S
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