Senior Gen AI/Agentic AI Engineer

About this role

<p>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.</p> <p><strong>Hard Skills:</strong></p> <ul> <li>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.</li> <li>Knowledge of ML/GenAI frameworks: LangGraph or LangChain, PyTorch / TensorFlow, Hugging Face, OpenAI/Anthropic SDK.</li> <li>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).</li> <li>Deep understanding of how LLMs interact with external APIs via Function Calling.</li> <li>Experience with vector databases, semantic search methods, and principles of database structuring and cleaning.</li> <li>Practical experience with at least one cloud platform (AWS, GCP, or Azure).</li> <li>Proficiency in Python and understanding of asynchronous programming.</li> <li>Understanding of the AI model lifecycle: monitoring, versioning, and quality evaluation (RAGAS, DeepEval), with hands-on experience using these tools.</li> <li>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.</li> <li>Deterministic Logic Integration — running AI agents on strict schemas to prevent the model from "making things up."</li> <li>A plus: knowledge of automated testing approaches for evaluating responses across large datasets to measure hallucination rates before MVP launch.</li> <li>Knowledge of Human-in-the-loop mechanisms, ensuring agents cannot execute actions without final user verification.</li> <li>Ability to design memory systems that store context from a client's previous conversations and operations for personalization (Long-term Memory &amp; User Context).</li> </ul> <p><strong>Soft Skills:</strong></p> <ul> <li>Ability to clearly communicate complex technical concepts and mentor team members.</li> <li>Ability to quickly test and evaluate new libraries and approaches.</li> <li>Analytical problem solving - debugging complex "black boxes" and understanding why an agent behaves unpredictably.</li> <li>Focus on delivering a working prototype rather than a perfect research paper.</li> <li>Close collaboration with Frontend and Backend developers to seamlessly integrate AI agents into the required environment.</li> </ul><div class="content-conclusion"><p><strong>We offer*:</strong></p> <ul> <li>Flexible working format - remote, office-based or flexible</li> <li>A competitive salary and good compensation package</li> <li>Personalized career growth</li> <li>Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)</li> <li>Active tech communities with regular knowledge sharing</li> <li>Education reimbursement</li> <li>Memorable anniversary presents</li> <li>Corporate events and team buildings</li> <li>Other location-specific benefits</li> </ul> <p>*not applicable for freelancers</p></div>