AI Engineer

toogeza

full-time

Posted on: 9/25/2025

Origin: • 🇪🇺 Anywhere in Europe

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Mid-LevelSenior

AWSAzureCloudDockerGoogle Cloud PlatformPython

About the role

Design and deliver real-world AI systems, working hands-on with LLMs, vector search, and prompt engineering.
Integrate vision and speech models to extend AI solutions beyond text into multimodal tasks.
Aggregate knowledge across text, images, and audio into coherent outputs.
Build agentic systems that can plan, reason, and act on data, combining, tuning, and deploying existing AI solutions into production-ready systems.
Drive R&D projects from design to deployment in iterative improvement cycles.
Build rapid prototypes, validate hypotheses, and integrate AI blocks into user-focused applications and data pipelines.
Design and implement LLM-based features such as document understanding, content summarization, and interactive Q&A.
Develop agentic AI workflows combining reasoning, tool calling, memory management, and context engineering to automate complex tasks.
Leverage RAG, vector databases, chunking techniques, and hybrid search methods for efficient information retrieval.
Integrate monitoring and evaluation best practices to track AI model performance, control costs, and ensure observability.
Fine-tune and adapt pre-trained models to meet specific project needs.
Collaborate closely within a cross-functional R&D team to bring AI solutions to production.

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
3+ years in AI engineering with a strong portfolio of real-world projects.
Strong hands-on experience with LLMs including prompt engineering, RAG implementations, AI agents, evaluation, observability, fine-tuning pre-trained models, 3rd party hosted providers and local LLMs.
Experience with vision and speech modalities for classification, generation, document understanding and transcription.
Proficient in Python and relevant AI frameworks (e.g., LangChain, LangGraph, LlamaIndex, OpenAI SDK, Hugging Face Transformers).
VCS (GitHub, GitLab) experience.
Cloud development and deployment experience on AWS, GCP, or Azure.
Deployment skills for AI services via APIs or batch workflows, including containerization with Docker.
Excellent problem-solving skills.
Commitment to continuous learning and following state-of-the-art research.
Team-oriented with a collaborative mindset.
Strong communication and presentation skills for technical and non-technical audiences.
Upper-Intermediate English level.