AI Engineer (all genders)

At PRODYNA, we design, implement, and operate custom software applications for mid- to large-sized enterprises. We help our clients build innovative, future-proof solutions through digitalization and cloud computing. As a member of the Cloud Native Computing Foundation (CNCF), we promote speed, agility, and scalability in software development.

As an AI Engineer at PRODYNA, you will design, build, and operate production-grade AI solutions combining robust backend engineering with modern LLM capabilities. Working with international clients and multidisciplinary teams, you’ll turn business needs into secure, scalable, and observable applications—from RAG and agentic workflows to APIs, evaluation pipelines, and LLMOps. The role is ideal for an engineer who approaches AI as a software engineering discipline: measurable, testable, cost-aware, and built for real-world use.

Your tasks

• Designing and conceptualizing modern data platforms for large-scale data integration and processing.
• Planning and implementing backend services using modern frameworks for data provisioning and utilization.
• Independently optimizing pipelines and integrating them into cloud platforms.
• Implementing tools and solutions to ensure data quality, data cleansing, and provision of aggregated data for analysis.
• Gathering and specifying requirements from our clients.

Your profile

• Several years of experience in software development, particularly in data-driven projects, data warehousing, or data platform construction.
• Skilled in developing pipelines and data integration routes both on-premises and in the cloud (ETL/ELT, Azure Data Factory, DBT, stored procedures, or similar tools).
• Familiarity with data modeling and experience with Data Vault, Data Mesh, Kimball, or Inmon methodologies.
• Proficiency in SQL and at least one programming language (e.g., Python, Scala).
• Experience with cloud platforms (e.g., Azure, AWS, or GCP).
• Strong analytical and problem-solving skills.
• Additional knowledge of data science or business intelligence (reporting tools) is an advantage.

Nice to have:

• Experience with Microsoft Fabric or understanding of the Fabric ecosystem.
• Knowledge of Delta Lake, Lakehouse architecture, and data mesh principles.
• Familiarity with CI/CD for data pipelines.
• Exposure to data cataloging tools (e.g., Purview, Alation).
• Understanding of privacy regulations (e.g., GDPR, CCPA).