Senior Fullstack Data Scientist – GenAI / LLM / RAG
Description
Wynagrodzenie
B2B: 27000 – 29000 PLN / mies. netto
Senovo IT is looking for an experienced Senior Fullstack Data Scientist to join an enterprise GenAI programme focused on building production-ready solutions using LLMs, RAG, AI Agents and modern Generative AI frameworks.
Location: Poland – 100% Remote
Contract: B2B
Language: English only
The Role
You will work across the full GenAI development lifecycle — from discovery and architecture through hands-on development and production deployment. The role combines Data Science, Python engineering and GenAI solution design, with a strong focus on RAG, LLM applications and AI agents.
Key Responsibilities
Design and deliver end-to-end Generative AI solutions based on LLMs, RAG and AI Agents.
Translate business requirements into scalable GenAI architectures.
Build RAG pipelines using vector databases, hybrid search, reranking and query transformation.
Develop GenAI applications using LangChain, LangGraph, LlamaIndex or similar frameworks.
Build production-grade backend/API components in Python.
Work with prompt engineering, model selection and fine-tuning including LoRA, QLoRA and SFT.
Implement LLM evaluation, validators, guardrails, PII controls and human-in-the-loop workflows.
Design and integrate MCP servers/clients for agent-based applications.
Integrate GenAI solutions with enterprise applications and cloud platforms.
Support technical estimations and architectural decisions.
Mentor Data Scientists and Engineers and contribute to reusable GenAI components and best practices.
What We're Looking For
6+ years of experience in Data Science / AI Engineering.
4+ years of production-grade Python development within AI/ML projects.
2+ years of commercial experience building production LLM / GenAI solutions.
Strong hands-on experience with RAG, LLMs, chatbots and AI Agents.
Experience with LangChain, LangGraph, LlamaIndex or similar GenAI frameworks.
Hands-on knowledge of MCP servers/clients.
Strong understanding of LLM evaluation, validators and guardrails.
Experience with vector databases, retrieval techniques and semantic/hybrid search.
Strong Python development skills including testing, packaging and production deployment.
Experience with Azure preferred, although AWS or GCP experience is also relevant.
Familiarity with CI/CD, Docker and containerised deployments.
Strong English communication skills.
Nice to Have
Experience with Spark, Databricks, Kubernetes, GitHub Actions, GitLab, Azure DevOps, multimodal models, multi-agent orchestration or other advanced Agentic AI frameworks.