
Healthcare Insurance âą SaaS âą B2C
DocPlanner is a global healthcare platform dedicated to improving the patient experience by helping them find the perfect doctor and book appointments easily. By creating an enjoyable patient journey, DocPlanner assists patients in accessing the best care possible anytime and anywhere. The company also offers doctors an integrated end-to-end solution to help manage their practices and improve their online reputation, allowing them to focus more on their patients. With a presence in 13 countries, including Poland, Brazil, and Spain, DocPlanner facilitates over 22 million appointments each month and hosts more than 90 million patient visits. It supports 260,000 active doctors, making it a leading healthcare platform with a strong international footprint.
September 30
đȘđž Spain â Remote
â° Full Time
đą Junior
đŁïž LLM Engineer
đ«đšâđ No degree required

Healthcare Insurance âą SaaS âą B2C
DocPlanner is a global healthcare platform dedicated to improving the patient experience by helping them find the perfect doctor and book appointments easily. By creating an enjoyable patient journey, DocPlanner assists patients in accessing the best care possible anytime and anywhere. The company also offers doctors an integrated end-to-end solution to help manage their practices and improve their online reputation, allowing them to focus more on their patients. With a presence in 13 countries, including Poland, Brazil, and Spain, DocPlanner facilitates over 22 million appointments each month and hosts more than 90 million patient visits. It supports 260,000 active doctors, making it a leading healthcare platform with a strong international footprint.
âą Join the global Machine Learning and Data Science unit and embed in the Noa product line used by doctors across multiple countries âą Support a product area within Noa to deliver end-to-end LLM capabilities âą Work alongside machine learning scientists, engineers, and country-specific linguists; report to the Head of Machine Learning & Data Science âą Design, deploy and iterate over LLM services for text-based applications and beyond âą Build small to medium-sized Python projects and collaborate on production code and deployments at scale âą Assess platform engineering and LLMOps bottlenecks; research and design scalable prompt management strategies âą Research, architect, and deploy LLM-powered information retrieval solutions (e.g., RAG) for complex multilingual environments âą Partner with the AI Platform team to refine LLMOps best practices, evolve frameworks, and establish scalable workflows âą Deliver initiatives that directly contribute to business objectives and iterate from prototype to production
âą At least one year of professional experience in LLM development or integration in a fast-paced, product-driven tech environment âą Demonstrated expertise in production-grade LLM deployments, including prompt management systems, vector databases, semantic search implementation, and API integration with foundation models âą Good understanding of transformer architectures âą Proficiency in LLM frameworks such as LangChain, LlamaIndex, or similar tools âą Proficiency in Python âą Experience in collaborative project development and good engineering practices âą Proven experience in evaluating LLMs through systematic testing, benchmark design, and development of custom metrics (accuracy, consistency, factuality, bias) âą Proven ability to integrate, deploy, and optimize large language models in production-grade environments ensuring scalability and robust performance âą Strong knowledge in prompt engineering, agent-based workflows, and generation/manipulation of embeddings âą Experience with RAG (Retrieval-Augmented Generation) techniques, vector similarity search, and information retrieval methods âą Problem-solving mindset, adaptability, and ability to manage timelines and deliver under tight deadlines âą Curiosity and eagerness to collaborate with cross-functional teams
âą A salary adequate to your experience and skills. âą Flexible remuneration and benefits system via Flexoh (restaurant card, transportation card, kindergarten, and training tax savings) âą Share options plan after 6 months of working with us âą Remote or hybrid work model with our hub in Barcelona âą Flexible working hours âą Summer intensive schedule during July and August (work 7 hours, finish earlier) âą 23 paid holidays, with exchangeable local bank holidays âą Additional paid holiday on your birthday or work anniversary âą Private healthcare plan with Adeslas for you and subsidized for your family (medical and dental) âą Access to hundreds of gyms for a symbolic fee in partnership with Wellhub for you and your family âą Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling âą Free English classes âą Equal opportunities in hiring and adaptable recruitment process
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