Senior Gen AI/Agentic AI Engineer

We're looking for an engineer with hands-on experience building and evaluating GenAI services - from RAG and agentic reasoning systems to production-grade LLM deployments. You'll work closely with Frontend and Backend teams to bring AI agents into real products, with a strong focus on reliability, safety, and shipping working prototypes fast. Hard Skills: - Practical experience developing and evaluating GenAI services, including RAG systems, understanding of the "ReAct" (Reasoning + Acting) paradigm and Agentic RAG, LLM API integration, and prompt/context engineering, as well as training, fine-tuning, and deploying ML models in production environments. - Knowledge of ML/GenAI frameworks: LangGraph or LangChain, PyTorch / TensorFlow, Hugging Face, OpenAI/Anthropic SDK. - Practical commercial experience working with AI models via API (Gemini, Anthropic) and self-hosted models (Llama 3, Mistral, Mixtral), with an understanding of model differences based on functional/non-functional requirements (FR/NFR). - Deep understanding of how LLMs interact with external APIs via Function Calling. - Experience with vector databases, semantic search methods, and principles of database structuring and cleaning. - Practical experience with at least one cloud platform (AWS, GCP, or Azure). - Proficiency in Python and understanding of asynchronous programming. - Understanding of the AI model lifecycle: monitoring, versioning, and quality evaluation (RAGAS, DeepEval), with hands-on experience using these tools. - Experience with Guardrails: setting hard constraints on conversation topics and agent actions, filters that automatically strip personal data before sending requests to external LLMs, and the ability to build output filters that fact-check generated responses before they're displayed. - Deterministic Logic Integration — running AI agents on strict schemas to prevent the model from "making things up." - A plus: knowledge of automated testing approaches for evaluating responses across large datasets to measure hallucination rates before MVP launch. - Knowledge of Human-in-the-loop mechanisms, ensuring agents cannot execute actions without final user verification. - Ability to design memory systems that store context from a client's previous conversations and operations for personalization (Long-term Memory & User Context). Soft Skills: - Ability to clearly communicate complex technical concepts and mentor team members. - Ability to quickly test and evaluate new libraries and approaches. - Analytical problem solving - debugging complex "black boxes" and understanding why an agent behaves unpredictably. - Focus on delivering a working prototype rather than a perfect research paper. - Close collaboration with Frontend and Backend developers to seamlessly integrate AI agents into the required environment. We offer*: - Flexible working format - remote, office-based or flexible - A competitive salary and good compensation package - Personalized career growth - Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) - Active tech communities with regular knowledge sharing - Education reimbursement - Memorable anniversary presents - Corporate events and team buildings - Other location-specific benefits *not applicable for freelancers