Senior Fullstack Data Scientist, REMOTE WARSAW

· 6+
years of experience in Data Science/AI engineering

· At
least 4+ years of experience in production-ready Python AI-related code
development.

· At
least 2+ years of experience in production-ready LLM-related code development,
preferably based on the Retrieval-Augmented Generation (RAG) concept.

· Strong
analytical and problem-solving skills with the ability to optimize AI solutions
for diverse applications.

· Strong
knowledge and experience in Generative AI, including LLMs, chatbots, AI agents,
and RAG mechanisms.

· Deep
understanding of LLM evaluators, validators, and guardrails.

· Hands‑on
experience with one or more 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

· Solid
understanding of ML/AI concepts: types of algorithms, machine learning
frameworks, model efficiency metrics, model lifecycle, AI architectures.

· Proven
ability to collaborate effectively across technical and non-technical teams.

· Familiarity
with cloud environments such as Azure (preferred), GCP, or AWS, including
AI-related managed services.

· Familiarity
with CI/CD, testing, and containerized deployments.

· Excellent
communication skills in English, with the ability to convey complex technical
concepts to various audiences.

Nice-to-Have Skills & Knowledge:

· Experience
in designing and programming ML algorithms and data processing pipelines using
Python.

· Good
understanding of CI/CD and DevOps concepts, with experience working with
selected tools (preferably GitHub Actions, GitLab, or Azure DevOps).

· Experience
in productizing ML solutions using technologies like Spark/Databricks or
Docker/Kubernetes.

· Experience
with agentic AI development frameworks (e.g., BMAD, multi‑agent orchestration,
spec‑driven AI workflows).

• Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites.
• “Office as an option” model. You can choose to work remotely or in the office.
• Workation. Enjoy working from inspiring locations in line with our workation policy.
• Great Place to Work® certified employer.
• Flexibility regarding working hours and your preferred form of contract.
• Comprehensive online onboarding program with a “Buddy” from day 1.
• Cooperation with top-tier engineers and experts.
• Unlimited access to the Udemy learning platform from day 1.
• Certificate training programs. Lingarians earn 500+ technology certificates yearly.
• Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
• Grow as we grow as a company. 76% of our managers are internal promotions.
• A diverse, inclusive, and values-driven community.
• Autonomy to choose the way you work. We trust your ideas.
• Create our community together. Refer your friends to receive bonuses.
• Activities to support your well-being and health.
• Plenty of opportunities to donate to charities and support the environment.
• Modern office equipment. Purchased for you or available to borrow, depending on your location.

,[Lead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine tuning, agents, guardrails), Build end to end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed., Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness., Perform model selection, prompting strategies, and fine tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing., Implement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human in the loop review where required)., Collaborate with data engineers, product owners, and full stack developers on scalable architectures, SLAs, and integration with existing enterprise systems, Gather technical requirements and estimate planned work., Mentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components., Stay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.] Requirements: Python, Data science, LLM, AI