Middle DevOps

About the Position

We’re looking for a DevOps / MLOps Engineer who is genuinely interested in AI-driven products and wants to grow with us. In this role, you will help operationalize AI solutions in production by applying solid DevOps, infrastructure, and solution architecture practices.

Responsibilities7

• Build, automate, and maintain a reliable high-load platform.
• Implement, configure and deploy infrastructure components using Ansible and Terraform.
• Work closely with Development and Machine Learning (Data Science) teams to launch new solutions (products) and improve existing ones.
• Support operational stability, participate in troubleshooting, and respond reliably to on-call issues.
• Maintain and improve non-production integration environments, providing them as an internal service for engineering teams.
• Drive automation across infrastructure and deployment processes to improve speed, quality, and reliability.
• Help establish operational standards, platform best practices, and effective collaboration between teams.

Requirements11

• 3+ years of experience in DevOps / Platform Engineering / Infrastructure roles.
• Strong hands-on experience with Ansible and Terraform.
• Practical experience with AWS.
• Good hands-on experience with Docker and Linux administration, preferably RHEL-based systems.
• Solid understanding of core Ops and infrastructure principles: networking, OSI model, load balancing, high availability, clustering, virtualization, observability, troubleshooting, and system reliability.
• Experience designing and improving CI/CD processes, preferably with Git and Jenkins.
• Understanding of how to build and operate production-grade environments, including non-production platforms used by engineering teams.
• Ability to work closely with developers, ML engineers, and data scientists: translate needs into practical solutions, and maintain healthy collaboration across teams.
• Strong communication skills, ownership mindset, proactive attitude, and readiness to learn new technologies independently.
• Experience or strong interest in AI/ML infrastructure, model deployment, monitoring, and MLOps practices.
• Practical Python knowledge for scripting and issue investigation.

Benefits7

• Career development and internal training programs that bring new knowledge and growth opportunities every day
• A professional and friendly team that supports and inspires, where your ideas matter
• Flexible schedule and remote work options to combine efficiency with comfort
• Wellbeing support: table tennis, psychological and legal assistance
• Participation in the bank’s social projects that make the world better and give meaning to your daily work
• A culture of trust and support where mistakes are seen as lessons and successes are celebrated together
• Modern tools and technologies to work efficiently and with pleasure