GenAI Full-Stack Scientist: End-to-End LLM Pipelines

Lever, Inc.

Polska

In loco

PLN 210.000 - 380.000

Tempo pieno

2 giorni fa

Candidati tra i primi

Generatore di candidature

Non inviare un curriculum generico — genera un curriculum e una lettera di presentazione personalizzati per questo specifico impiego.

Supera i filtri ATS

Descrizione del lavoro

Lever, Inc. is seeking a senior Data Science/AI Engineer in Poland to lead GenAI initiatives from problem framing to production-grade solutions. You will design architectures, build end-to-end applications with RAG pipelines, and collaborate across data, product, and engineering teams.

Strong Python skills and hands-on GenAI framework experience are essential. You will also mentor peers, implement governance and safety controls, and stay updated on evolving GenAI trends, enabling scalable,

Competenze

6+ years of experience in Data Science/AI engineering.
At least 4+ years of production-ready Python AI-related code development.
At least 2+ years of production-ready LLM-related code development, preferably RAG-based.
Strong analytical and problem-solving skills with the ability to optimize AI solutions.
Solid knowledge of Generative AI including LLMs, chatbots, AI agents, and RAG mechanisms.
Hands-on experience with GenAI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration stacks.
Hands-on experience designing or operating MCP servers/clients for LLM agents.
Strong Python skills including production-grade code, packaging, and testing for data/ML services.
Familiarity with cloud environments (Azure/GCP/AWS) and AI-related managed services.
CI/CD, testing, and containerized deployments.
Excellent communication skills in English.

Mansioni

Lead discovery and solution design for GenAI use cases, translating business problems into architectures.
Build end-to-end GenAI applications: data ingestion, retrieval layer, orchestration, API/backend, and UI.
Design and implement RAG pipelines with vector databases and hybrid search.
Perform model selection, prompting strategies, and fine-tuning for various models.
Implement safety, compliance, and governance controls with audit logs and human-in-the-loop where required.
Collaborate with data engineers, product owners, and full-stack developers on scalable architectures and SLAs.
Gather technical requirements and estimate planned work.
Mentor other data scientists/engineers in GenAI best practices; contribute to internal libraries.
Stay current with GenAI landscape and perform targeted PoCs.