AI DevOps

Upvanta is seeking an AI DevOps professional with experience in DevOps, cloud, and automation, particularly with Microsoft Azure, Kubernetes/OpenShift, and AI/ML solutions.

• Willingness to work from the office in Wrocław one day per month.
• Minimum 5 years of experience in IT, particularly in software development, DevOps, cloud, or related areas.
• Practical knowledge of DevOps and CI/CD.
• Experience with cloud solutions, preferably Microsoft Azure.
• Experience with containerization and orchestration, especially Kubernetes or OpenShift.
• Practical experience building, integrating, or deploying AI/ML or automation solutions.
• Ability to work at the intersection of business and technology.
• Knowledge of IT security and data processing in regulated environments.
• Ability to analyze processes and identify automation opportunities.
• Independence, proactivity, and practical problem-solving approach.

Nice to have:

• Good knowledge of Microsoft Azure, including environment parameterization, configuration, and hardening.
• Programming experience in Python, Java, or C#.
• Experience in regulated organizations, e.g., financial sector.
• Knowledge of MLOps and tools supporting AI/ML model lifecycle.
• Experience with low-code/no-code solutions for process automation.
• Certifications related to Azure, DevOps, or AI/ML.
• Knowledge of best practices in AI security and management.

• Designing and implementing AI/ML solutions supporting business processes.
• Identifying processes for automation or optimization using AI.
• Integrating AI models and services with existing IT systems and business applications.
• Building and maintaining CI/CD pipelines for AI solutions.
• Deploying and managing solutions in cloud environments, especially Microsoft Azure.
• Automating deployment and operational processes in collaboration with DevOps teams.
• Configuring, monitoring, and optimizing environments running AI solutions.
• Ensuring security, data protection, and compliance with regulations such as GDPR and AI Act.
• Optimizing performance and costs of AI solutions and infrastructure.
• Documenting and standardizing processes and technical solutions.
• Collaborating with business units to translate organizational needs into technology solutions.