# Fullstack Senior Data Scientist - Lingaro [Lingarogroup](https://gurify.com/jobs?q=Lingarogroup) · Poland · Posted 6 months ago Senior [Full Stack](https://gurify.com/jobs/fullstack) [Data](https://gurify.com/jobs/data) [Apply on the original posting → (opens in a new tab)](https://jobs.lever.co/lingarogroup/03c58014-85e9-4809-8669-d5bc810a0d36/apply?lever-source%5b%5d=Jobgether) ## Job description We are looking for a skilled and experienced Fullstack Data Scientist with solid expertise in Generative AI (GenAI) to lead projects focused on building and implementing advanced systems based on Large Language Models (LLMs), chatbots, AI agents, and Retrieval-Augmented Generation (RAG) mechanisms. As a Senior Data Scientist, you will be responsible for designing, implementing, and optimizing GenAI solutions, as well as mentoring teams. Your knowledge and experience will be crucial in making architectural decisions, selecting technologies, and implementing best practices in AI-driven development. Tasks: 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. What We're Looking For: 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. What Will Set You Apart: 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). We are looking for a skilled and experienced Fullstack Data Scientist with solid expertise in Generative AI (GenAI) to lead projects focused on building and implementing advanced systems based on Large Language Models (LLMs), chatbots, AI agents, and Retrieval-Augmented Generation (RAG) mechanisms. As a Senior Data Scientist, you will be responsible for designing, implementing, and optimizing GenAI solutions, as well as mentoring teams. Your knowledge and experience will be crucial in making architectural decisions, selecting technologies, and implementing best practices in AI-driven development. Tasks: 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. What We're Looking For: 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. What Will Set You Apart: 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). **Live in Lingarogroup’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role. We remove it as soon as it disappears at source. ## More jobs like this - AS [Fullstack Engineer in Warsaw • Asana Jobs](https://gurify.com/job/fullstack-engineer-in-warsaw-asana-jobs-37064c10c804) Asana · Warsaw · 2 months ago - LI [Full Stack / Data Engineer](https://gurify.com/job/full-stack-data-engineer-at-lineten-97054c283b8d) Lineten · 3 weeks ago - VA [Senior Fullstack Software Engineer, Authoring Experience](https://gurify.com/job/senior-fullstack-software-engineer-authoring-experience-at-vanta-75eaf8d21506) Vanta · Remote U.S. · 3 days ago - AW [Senior Full-Stack Engineer (f/m/d)](https://gurify.com/job/senior-full-stack-engineer-f-m-d-at-awin-060b092390e4) Awin · Iași, Poland · 2 months ago - SI [Senior Fullstack Developer (.NET Angular)](https://gurify.com/job/senior-fullstack-developer-net-angular-at-singu-3aa73657d704) Singu · Poland - Cracow · 4 weeks ago - TO [Senior Full Stack Engineer](https://gurify.com/job/senior-full-stack-engineer-at-toggl-0328f4513c1c) Toggl · Belgrade, Serbia · yesterday ```json {"@context":"https://schema.org/","@type":"JobPosting","title":"Fullstack Senior Data Scientist - Lingaro","description":"\u003Cp\u003EWe are looking for a skilled and experienced Fullstack Data Scientist with solid expertise in Generative AI (GenAI) to lead projects focused on building and implementing advanced systems based on Large Language Models (LLMs), chatbots, AI agents, and Retrieval-Augmented Generation (RAG) mechanisms. As a Senior Data Scientist, you will be responsible for designing, implementing, and optimizing GenAI solutions, as well as mentoring teams. Your knowledge and experience will be crucial in making architectural decisions, selecting technologies, and implementing best practices in AI-driven development.\u0026#160;\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003ETasks:\u003Cbr /\u003ELead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine-tuning, agents, guardrails).\u003Cbr /\u003EBuild end-to-end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.\u003Cbr /\u003EDesign and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.\u003Cbr /\u003EPerform model selection, prompting strategies, and fine-tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing.\u003Cbr /\u003EImplement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human-in-the-loop review where required).\u003Cbr /\u003ECollaborate with data engineers, product owners, and full-stack developers on scalable architectures, SLAs, and integration with existing enterprise systems.\u003Cbr /\u003EGather technical requirements and estimate planned work.\u003Cbr /\u003EMentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components.\u003Cbr /\u003EStay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003EWhat We\u0026#39;re Looking For:\u003Cbr /\u003E6\u002B years of experience in Data Science/AI engineering.\u003Cbr /\u003EAt least 4\u002B years of experience in production-ready Python AI-related code development.\u003Cbr /\u003EAt least 2\u002B years of experience in production-ready LLM-related code development, preferably based on the Retrieval-Augmented Generation (RAG) concept.\u003Cbr /\u003EStrong analytical and problem-solving skills with the ability to optimize AI solutions for diverse applications.\u003Cbr /\u003EStrong knowledge and experience in Generative AI, including LLMs, chatbots, AI agents, and RAG mechanisms.\u003Cbr /\u003EDeep understanding of LLM evaluators, validators, and guardrails.\u003Cbr /\u003EHands-on experience with one or more GenAI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration stacks.\u003Cbr /\u003EHands-on experience designing or operating MCP servers/clients for LLM agents\u003Cbr /\u003EStrong Python skills, including production-grade code, packaging, and testing for data/ML services\u003Cbr /\u003ESolid understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model lifecycle, AI architectures.\u003Cbr /\u003EProven ability to collaborate effectively across technical and non-technical teams.\u003Cbr /\u003EFamiliarity with cloud environments such as Azure (preferred), GCP, or AWS, including AI-related managed services.\u003Cbr /\u003EFamiliarity with CI/CD, testing, and containerized deployments.\u003Cbr /\u003EExcellent communication skills in English, with the ability to convey complex technical concepts to various audiences.\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003EWhat Will Set You Apart:\u003Cbr /\u003EExperience in designing and programming ML algorithms and data processing pipelines using Python.\u003Cbr /\u003EGood understanding of CI/CD and DevOps concepts, with experience working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps).\u003Cbr /\u003EExperience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.\u003Cbr /\u003EExperience with agentic AI development frameworks (e.g., BMAD, multi-agent orchestration, spec-driven AI workflows).\u003C/p\u003E\u003Cp\u003EWe are looking for a skilled and experienced Fullstack Data Scientist with solid expertise in Generative AI (GenAI) to lead projects focused on building and implementing advanced systems based on Large Language Models (LLMs), chatbots, AI agents, and Retrieval-Augmented Generation (RAG) mechanisms. As a Senior Data Scientist, you will be responsible for designing, implementing, and optimizing GenAI solutions, as well as mentoring teams. Your knowledge and experience will be crucial in making architectural decisions, selecting technologies, and implementing best practices in AI-driven development.\u0026#160;\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003ETasks:\u003Cbr /\u003ELead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine-tuning, agents, guardrails).\u003Cbr /\u003EBuild end-to-end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.\u003Cbr /\u003EDesign and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.\u003Cbr /\u003EPerform model selection, prompting strategies, and fine-tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing.\u003Cbr /\u003EImplement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human-in-the-loop review where required).\u003Cbr /\u003ECollaborate with data engineers, product owners, and full-stack developers on scalable architectures, SLAs, and integration with existing enterprise systems.\u003Cbr /\u003EGather technical requirements and estimate planned work.\u003Cbr /\u003EMentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components.\u003Cbr /\u003EStay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003EWhat We\u0026#39;re Looking For:\u003Cbr /\u003E6\u002B years of experience in Data Science/AI engineering.\u003Cbr /\u003EAt least 4\u002B years of experience in production-ready Python AI-related code development.\u003Cbr /\u003EAt least 2\u002B years of experience in production-ready LLM-related code development, preferably based on the Retrieval-Augmented Generation (RAG) concept.\u003Cbr /\u003EStrong analytical and problem-solving skills with the ability to optimize AI solutions for diverse applications.\u003Cbr /\u003EStrong knowledge and experience in Generative AI, including LLMs, chatbots, AI agents, and RAG mechanisms.\u003Cbr /\u003EDeep understanding of LLM evaluators, validators, and guardrails.\u003Cbr /\u003EHands-on experience with one or more GenAI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration stacks.\u003Cbr /\u003EHands-on experience designing or operating MCP servers/clients for LLM agents\u003Cbr /\u003EStrong Python skills, including production-grade code, packaging, and testing for data/ML services\u003Cbr /\u003ESolid understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model lifecycle, AI architectures.\u003Cbr /\u003EProven ability to collaborate effectively across technical and non-technical teams.\u003Cbr /\u003EFamiliarity with cloud environments such as Azure (preferred), GCP, or AWS, including AI-related managed services.\u003Cbr /\u003EFamiliarity with CI/CD, testing, and containerized deployments.\u003Cbr /\u003EExcellent communication skills in English, with the ability to convey complex technical concepts to various audiences.\u003Cbr /\u003E\u0026#160;\u003Cbr /\u003EWhat Will Set You Apart:\u003Cbr /\u003EExperience in designing and programming ML algorithms and data processing pipelines using Python.\u003Cbr /\u003EGood understanding of CI/CD and DevOps concepts, with experience working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps).\u003Cbr /\u003EExperience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.\u003Cbr /\u003EExperience with agentic AI development frameworks (e.g., BMAD, multi-agent orchestration, spec-driven AI workflows).\u003C/p\u003E","identifier":{"@type":"PropertyValue","name":"Gurify","value":"fullstack-senior-data-scientist-lingaro-at-lingarogroup-afef0ffb583d"},"url":"https://gurify.com/job/fullstack-senior-data-scientist-lingaro-at-lingarogroup-afef0ffb583d","datePosted":"2026-02-16","validThrough":"2026-10-13T23:59:59Z","hiringOrganization":{"@type":"Organization","name":"Lingarogroup","sameAs":"https://jobs.lever.co/lingarogroup"},"directApply":false,"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressCountry":"PL"}}} ``` ```json {"@context":"https://schema.org/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Jobs","item":"https://gurify.com/jobs"},{"@type":"ListItem","position":2,"name":"Poland","item":"https://gurify.com/jobs/poland"},{"@type":"ListItem","position":3,"name":"Fullstack Senior Data Scientist - Lingaro","item":"https://gurify.com/job/fullstack-senior-data-scientist-lingaro-at-lingarogroup-afef0ffb583d"}]} ```