Systems / DevOps Engineer

SOFTSWISS·Удалённо·Удалённо·сегодня

SOFTSWISS is hiring a Systems Engineer / DevOps Engineer to join our Infrastructure & Platform Team. You will work on designing, building, and scaling reliable cloud infrastructure and CI/CD ecosystems, contributing to the stability and performance of our products across global markets.

You will design, build, and optimise scalable infrastructure and deployment pipelines to ensure high system reliability, performance, and security across our platforms. Your work will impact service uptime and delivery speed by enabling efficient CI/CD processes, improving observability, and supporting development teams in releasing high-quality features faster.

Collaboration with product teams.
Participate in the launch of new projects and new features.
Participate in the design of complex information systems.
Automate infrastructure components.
Setup and maintain infrastructure.
Consult managers and company clients.
Create and maintain technical documentation.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
At least 3 years of professional experience in systems engineering or a similar role such as SRE or DevOps.
Proficient with Linux-based operating systems.
Experience with configuration management systems (Puppet / Chef / Ansible / Saltstack).
Development skills in bash and python.
Experience with container application virtualization systems and orchestration systems for them (preferably with k8s).
Good knowledge and experience in the CI/CD process (Gitlab CI).
Experience with distributed systems.
Experience in information system design.
Experience with Postgresql.
Excellent command of Russian.
Intermediate or higher English (B1+).
Familiarity with modern AI-powered tools and their use in daily engineering workflows:
a. Experience with agentic tools (e.g., Claude Code, Cursor, etc.), not just chat interfaces: ability to assign tasks to agents and work with MCP integrations (Jira, GitLab, etc).
b. Ability to validate AI-generated output: reviewing generated merge requests and configurations, understanding where an agent can be given autonomy and where a human approval gate is required (e.g., irreversible actions, production environments).
c. Documentation for agents: ability to write structured runbooks and state files that are executable and understandable by both humans and AI. This is a core foundation of the project.
d. AI secrets hygiene: understanding what must never be exposed to a model or included in its context (tokens, credentials, PII, sensitive data).

Experience with major cloud service providers.
Experience with Go / Ruby language.
Architectural ability to participate in designing complex, highly available, and geo-distributed systems and the readiness to argue decisions.