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IT for Humans | Humans for IT
Over 30 years of experience in IT!
Expertise you can trust!
Senior AI Engineer (Generative AI Focus)
Europe
Remote
B2B
6,000 - 10,000 Euro/Month
Our Client is a long-established and highly-regarded Central and Eastern European technology provider specialising in designing, building, and operating advanced, mission-critical software solutions for large international organisations. With over 25 years of history and a team of 600+ top-tier software engineers across Europe, they are a certified partner for high-stakes industries including Aerospace & Defence, Automotive, Telecommunications, and Financial Services. They hold rigorous quality and security certifications such as NATO AQAP and TISAX.
This specific role involves working with a leading European client to develop and maintain their sophisticated cloud platform. You will be responsible for defining the DevOps architecture and strategy for solutions built primarily on Microsoft Azure and Kubernetes. You will be a key player in ensuring that highly available, scalable, and secure cloud-native architectures are implemented, managing the full lifecycle from Infrastructure as Code (IaC) development through to CI/CD and observability. This is a chance to apply your senior expertise to complex, enterprise-grade cloud environments.
Resposibilities
As a Senior AI Engineer, you will be a technical leader responsible for the end-to-end lifecycle of Generative AI solutions. Your key tasks will include:
Generative AI Solution Design: Architect, design, and implement advanced Generative AI applications (e.g., Conversational AI, Generative UI, Integrated Agentic RAG systems) to meet complex client requirements.
Large Language Model (LLM) Customisation: Lead the process of fine-tuning, prompt engineering, and customising state-of-the-art Large Language Models (LLMs) and foundation models for specific languages, domains, and modalities.
Production Deployment and Scaling: Take responsibility for translating Proof-of-Concepts (PoCs) into secure, scalable, and high-performance production solutions, utilising best practices in MLOps and cloud platforms.
RAG System Development: Design and build robust Retrieval-Augmented Generation (RAG) pipelines and integrated agentic systems that seamlessly connect LLMs with enterprise knowledge bases and data sources.
Code Quality and Standards: Act as a champion for engineering best practices, conducting code reviews and ensuring all models and applications adhere to high standards for stability, performance, and explainability.
Client and Stakeholder Engagement: Work directly with product owners, data scientists, and clients to validate business cases, define requirements, and provide deep technical guidance on the strategic application of GenAI.
Research and Innovation: Stay abreast of the rapidly evolving AI landscape (transformers, new LLM architectures, optimisation techniques) and contribute to the technical roadmap of the AI Factory platform
Requirments
Professional AI Experience: Extensive experience (5+ years) in a Software, ML, or AI Engineering role, with significant focus on Generative AI and Large Language Models (LLMs).
GenAI Concepts: Deep, hands-on knowledge of transformer architectures, embedding models, RAG systems, and prompt engineering techniques.
Programming Proficiency: Expert-level skills in Python and its associated AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face, or LangChain).
Software Engineering Principles: Proven experience in designing and implementing robust software architectures for large-scale platforms, including strong understanding of version control (Git) and testing methodologies.
MLOps and Cloud Deployment: Practical experience with MLOps principles and deploying ML models and pipelines on major cloud platforms (AWS, Azure, or GCP) using containerization (Docker) and orchestration tools (Kubernetes).
Data Handling: Strong background in data engineering, including working with Big Data technologies (e.g., Apache Spark) and ensuring data readiness for model training and fine-tuning.
Collaboration: Excellent communication and presentation skills, with the ability to articulate complex AI concepts to both technical and non-technical audiences.
Desirable Qualifications
Experience with advanced MLOps tools such as MLflow, Kubeflow, or Databricks.
Familiarity with techniques for model optimisation and deployment for high-performance inference.
A Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field.
Our Client offers
Our Client is committed to supporting your professional journey with a competitive package designed for growth, flexibility, and well-being.
100% Remote Work Option within Europe, providing ultimate work-life flexibility.
Flexible Working Hours and a hybrid work model, supported by modern office hubs across Europe.
Personalised Development Program and access to dedicated mentorship and coaching from domain experts to accelerate your career growth.
Comprehensive Benefits Package, including additional health insurance and food vouchers.
The chance to take full ownership and make a tangible impact on mission-critical, cloud-native solutions.
A supportive, collaborative team culture with regular social events and team-building activities.