Pre-Sales Engineer (AI & Big Data)

Undergraduate degree or higher in Computer Science, Data Science, Engineering, or related field – or equivalent hands-on experience., Proven experience in technical roles – e.g., exposure to AI/ML products, data platforms, consulting services, solution engineering, or cloud architecture., Foundational understanding of public cloud platforms (AWS, Azure, GCP) with experience deploying cloud-based AI solutions and/or modern data platform architectures., Comfortable working across multiple clients and projects, often in parallel, with strong organizational and time management skills., A strong foundational understanding of AI/ML workflows – from data preprocessing and model training to evaluation and deployment., Familiarity with LLM-based applications, including embeddings, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex)., Working knowledge of MLOps and orchestration tools like MLflow, Airflow, Kubeflow, Vertex AI, or SageMaker., Proficiency in Python and experience with common AI/ML libraries such as pandas, scikit-learn, PyTorch, or TensorFlow., Understanding of modern data architectures and data engineering concepts, including ETL/ELT pipelines, big data processing, and cloud data services (e.g., Azure Data Factory, Azure Synapse, Databricks, or similar platforms)., Strong communication skills, with the ability to simplify complex concepts for diverse audiences, including AI engineers, data scientists, data engineers, and non-technical stakeholders., Excellent English (at least C1 level)., Excellent time management and multitasking ability – comfortable working across several customer projects and internal teams., Exposure to or interest in sales processes, technical demos, and customer-facing engagements.

Reimbursement for prescription glasses or contact lenses, sharing the costs of sports activities, private medical care, sharing the costs of foreign language classes, sharing the costs of professional training & courses, remote work opportunities, flexible working time, fruits, integration events, no dress code, video games at work, coffee / tea, drinks, christmas gifts, birthday celebration, employee referral program