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.
You will work at the intersection of Data Science, Development, DevOps, and ML Engineering to build and evolve reliable infrastructure, improve delivery processes, productize AI solutions and integrate them into an existing business environment.
We follow DevOps principles to support continuous integration and continuous delivery, and we use Agile/Scrum practices to keep collaboration efficient and iterative.
As part of this project, you will contribute to AI adoption in the financial domain, including areas such as information security, fraud detection, customer service automation, and related internal platforms. This role offers a chance to work on practical, high-impact infrastructure challenges in a modern AI environment.
What is important for us
— 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.
Strong plus
Hands-on experience with one or several of the following technologies:
— RabbitMQ, Kafka
— PostgreSQL, MongoDB, Redis
— Nginx, Traefik
— ELK stack
— Prometheus, Grafana, Loki, Tempo
— Qdrant or other vector databases
— Vault, Consul, Keycloak
— VMware
— Kubernetes
Your responsibilities
— 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.
Why 7,000 Employees Have Chosen Us: * 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
