Artificial Intelligence Engineer

Job Description: Senior AI EngineerLocation: Helsinki, Finland (Onsite)Employment Type: [Full-Time / Contract]About the RoleWe are looking for an experienced AI Engineer with 5+ years of hands-on expertise in designing, building, and deploying scalable Artificial Intelligence and Generative AI solutions. In this role, you will bridge the gap between cutting-edge AI research and robust production systems, architecting autonomous AI agents, advanced Retrieval-Augmented Generation (RAG) pipelines, and efficient MLOps workflows.Key ResponsibilitiesGenerative AI & LLMs: Design, fine-tune, and integrate large language models (LLMs) and foundational models into enterprise applications.AI Agents & Automation: Build autonomous AI agents capable of complex decision-making, tool usage, and multi-step workflow execution.RAG Systems: Architect and optimize high-performance Retrieval-Augmented Generation (RAG) pipelines, embedding models, vector databases, and semantic search architectures.Prompt Engineering: Develop, test, and refine advanced prompt engineering strategies to maximize model accuracy, reliability, and safety.MLOps & Deployment: Implement robust MLOps pipelines for model monitoring, version control, evaluation, and scalable cloud deployment.Collaboration: Work closely with product, engineering, and data teams to translate business requirements into production-grade AI features.Required Qualifications & SkillsExperience: 5+ years of professional software engineering experience, with a strong, dedicated focus on AI/ML and Generative AI systems.Programming: Advanced proficiency in Python and modern AI/ML libraries/frameworks (e.g., LangChain, LlamaIndex, PyTorch, Hugging Face).Generative AI & LLMs: Deep practical knowledge of commercial and open-source LLMs, API integrations, and model fine-tuning.Advanced Architectures: Proven experience building multi-agent frameworks and production-ready RAG architectures using vector databases (e.g., Pinecone, Milvus, Qdrant, Chroma).Prompt Engineering: Mastery of prompt design, evaluation frameworks, and hallucination reduction techniques.MLOps & Infrastructure: Hands-on experience with MLOps tools, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, or Azure).Preferred QualificationsExperience with enterprise-grade security, data privacy, and compliance regarding LLM deployments.Contributions to open-source AI projects or active research background. If interested, please share your CV at [email protected]