AI Architect

Proven commercial experience in designing and implementing AI agents and agentic workflows (multi-step orchestration, tool usage, human-in-the-loop), using frameworks such as LangChain, AutoGen, or CrewAI., Hands-on knowledge of chatbot and voicebot architectures, RAG (Retrieval-Augmented Generation) solutions, and integrations via MCP., Practical experience with LLM services (OpenAI, Google Gemini, open-source models) and strong skills in prompt engineering., Experience in LLMOps, including observability, prompt management, and implementation of guardrails., Knowledge of at least one cloud platform (Azure, GCP, or AWS), including AI services and infrastructure management using IaC., Experience with model training and fine-tuning (LoRA / QLoRA, RLHF / DPO) and MLOps — at least at a conceptual level, with one production or implemented use case., Knowledge of AI security, including prompt injection mitigation, content filtering, and data privacy considerations in LLM-based systems., Strong Python skills, with the ability to build production-ready microservices (FastAPI, asyncio)., Presales capabilities: building prototypes (PoCs), presenting technical solutions to clients, and estimating scope and effort., Communicative English (ability to work with international clients)., Experience with cloud data platforms such as Databricks, Snowflake, or BigQuery., Knowledge of Kafka and event-driven architectures., Experience with backend technologies (Node.js, Go, Java) or frontend technologies (React, Next.js), enabling delivery of end-to-end demos or PoCs.

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