AI Senior Data Engineer

Telemedi is a company in the healthcare sector employing programmers, doctors, and experts from other fields to create modern solutions that facilitate patients' lives. Their goal is to use technology to provide everyone with convenient and immediate access to medical care. Telemedi operates in digital healthcare solutions, offering over 100,000 remote doctor consultations across more than 20 global markets with a team of over 500 general practitioners. Their services add significant economic value to insurance, assistance, healthcare, and financial companies in Europe, the Middle East, South and North America, including key global players such as AXA, Allianz, Generali, PZU, VIG, Mondial, Europ Assistance, and Novartis.

• Advanced skills in building solutions with LLMs, including autonomous workflows where agents decide which tools to invoke and perform tasks step-by-step, including evaluation, guardrails, and conscious trade-offs between cost and latency
• Strategic business curiosity: understanding the purpose of building, users, and business decisions based on your systems; ability to translate ambiguous commercial problems into concrete technological decisions
• Proficiency in SQL (including performance tuning and modeling for analytical loads) and Python
• Practical experience designing and maintaining modern reporting/BI stacks (Streamlit, Power BI, Metabase, or similar)
• Experience designing rigorous data validation and observability processes for AI-based pipelines
• Concrete AI portfolio demonstrating deployed solutions with real impact
• Comfort working autonomously, influencing stakeholders, and raising the bar for the team
• Ability to adapt to a dynamic and continuously evolving environment
• Fluent knowledge of Polish language

• Build architecture and implement autonomous production workflows that transform raw data into reporting and decision-making systems
• Map key business processes in collaboration with management and define strategies on what to automate using AI and what not to
• Develop the analytical layer of the telemedicine platform including roadmap, implementation, and maintenance
• Replace reporting processes with intelligent, scalable, and repeatable pipelines
• Design architecture for data validation systems, observability, and monitoring of AI results quality
• Define standards and best practices in AI/data area

Kolejność punktów nie jest przypadkowa. Pierwsze trzy będą stanowić 80% czasu Twojej pracy.