AI Engineer
Role details
Job location
Tech stack
Job description
We are looking for AI Engineering professionals across three complementary levels: strategic, tactical and operational. This single vacancy represents multiple profiles. Candidates may specialize in one or more of these areas. Our focus is on people who know how to apply Large Language Models (LLMs) and other modern AI technologies in practical business contexts. Experience ranges from solution design to implementation, optimization and operationalization. We welcome applicants with expertise across AI engineering, machine learning, deep learning, GenAI and process automation.
Strategic Profile
- Translate business ambitions into AI solution strategies.
- Shape solution design for AI initiatives, including architecture, delivery approach and governance.
- Develop vision, roadmaps and standards for AI adoption.
Tactical Profile
- Design solutions for AI, GenAI, ML and automation use cases.
- Define the end-to-end delivery process, including data flows, modelling approach, integration patterns and operational requirements.
- Guide teams in delivering high quality, scalable AI components.
Operational Profile
- Build, apply and integrate LLMs, ML and deep learning models into production systems.
- Develop Python based AI components, data pipelines and automation workflows.
- Execute model training, fine tuning, RAG pipelines, evaluation, deployment and monitoring.
What You'll Be Doing
- Provide technical leadership across AI projects, from ideas to delivery.
- Translate complex problems into experiments and actionable plans.
- Apply LLMs and GenAI techniques through API use, integration, optimisation and continuous improvement.
- Handle data preparation, model lifecycle, evaluation and production monitoring.
- Work with modern AI frameworks, SDKs and agent-based architectures.
- Contribute to solution design and the full delivery lifecycle for AI related products and services.
Requirements
Do you have experience in Python?, Do you have a Master's degree?, * Background in AI engineering, ML, deep learning and GenAI.
- Proven ability to deliver AI solutions with business impact.
- Experience applying LLMs in real world applications, including prompt engineering, fine tuning, RAG and evaluation.
- Strong Python skills and familiarity with AI frameworks such as PyTorch, Hugging Face, LangChain or similar.
- Experience integrating commercial and open source LLM APIs.
- Understanding of solution design principles, software engineering practices and Agile delivery.
- Strong communication skills and the ability to work with both technical and non technical stakeholders, driving progress.