IT Craft invites a AI/ML Python Developer to join our team. We’re looking for a specialist passionate about AI technologies, Large Language Models, and intelligent data processing. Your primary focus will be on developing and integrating AI-based solutions – from RAG systems and LLM integrations to API development and intelligent automation – contributing to projects across domains such as finance, healthcare, and knowledge management.
The role also involves experimenting with models, evaluating AI project requests during presale stages, and collaborating with backend and DevOps teams to deliver reliable, production-ready systems.
Requirements:
- 3 + years Python 3.x; strong proficiency with FastAPI/Django, LangChain/LangGraph; Git, CI/CD, Docker;
- Practical knowledge of leading models (GPT, Claude, Gemini, Mistral, Llama, Qwen, etc); working with them via public APIs, self-hosting, or managed platforms (AWS Bedrock, Azure OpenAI, GCP Vertex);
- Retrieval-Augmented Generation (RAG), Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (LoRA/QLoRA/PEFT), Reinforcement Learning from Human Feedback (RLHF), prompt engineering, and evaluation;
- Designing multi-turn conversational flows, tool invocation, agent routing/orchestration with LangChain, LangGraph, LlamaIndex, or similar;
- Experience with FAISS, Milvus /Chroma / Pinecone / pgvector / S3 vector (indexing, similarity search, hybrid search);
- Building and integrating Model Context Protocol (MCP) servers to securely expose domain tools/functions to LLMs;
- Advanced use of no-/low-code tools: n8n, Make (Integromat), Zapier (triggers, webhooks, custom modules);
- Ownership mindset, rapid prototyping, clear technical writing; English at Upper-Intermediate (B2) or higher;
Key Responsibilities:
- Design & build end-to-end LLM workflows in Python — from data ingestion to inference APIs;
- Implement RAG pipelines: document parsing, embedding generation, vector search, and evaluation;
- Create chatbots / autonomous agents with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or CrewAI;
- Expose tools via MCP servers so that external LLMs can invoke domain-specific actions;
- Integrate no-/low-code automation (n8n, Make, Zapier) to orchestrate business workflows;
Write clean, test-driven code; set up CI/CD; monitor, log, and continuously improve model performance and system reliability.
Nice to Have:
- Experience with data privacy & compliance (GDPR, SOC 2);
- Operate in cloud & on-prem (Docker, GPU instances, AWS Bedrock/Azure OpenAI, self-hosted LLMs, etc.);
- Hands-on experience with TensorFlow, PyTorch, NumPy, Pandas; ability to train, fine-tune, and evaluate ML/LLM models.
- Familiarity with front-end stacks (React/Next.js, TypeScript) for building AI-powered user interfaces;
- Bonus: Experience in Generative Graphics, including Stable Diffusion, Inpainting techniques, and ControlNets;
- Bonus: Experience in LLM hosting and working with llama.cpp.