Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale.
As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk.
Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.
About the Role
Veeam Data Cloud provides cloud-based data protection. Our Site Reliability Engineering team uses software, telemetry, and systems engineering to improve service reliability and make product changes safer to deliver.
As a Senior Software Engineer, Reliability, you will own specific services, tools, or components from design through production operation. You will use AI coding agents as part of the development workflow and apply your engineering judgment to the design, correctness, and reliability of the result.
The role combines planned software development with troubleshooting, maintenance, and incident response. You will work with Staff engineers and product teams to turn operational problems into lasting improvements in software and systems.
What You’ll Do
Build and ship production-ready reliability software using AI coding agents.
Break down problems, define requirements and acceptance criteria, guide implementation, review generated code, and validate changes through comprehensive testing Develop reusable libraries, services, controllers, Kubernetes components, infrastructure modules, and service templates for deployment checks, rate limiting, circuit breaking, and load management Build observability capabilities, including telemetry pipelines for metrics, logs, and traces, as well as SLIs, SLOs, and error-budget tooling that supports release decisions.
Design and implement safe-release capabilities, including canary deployments, automated checks, rollback mechanisms, and delivery-pipeline integrations Create fault-injection, failure-recovery, and load tests to identify resilience and performance issues before they affect production Design and improve distributed services, initially on Azure, with a focus on failure modes, graceful degradation, recovery, API quality, and production readiness Use metrics, logs, and traces to diagnose issues, validate releases, and keep alerts relevant and actionable Respond to and lead incidents during assigned coverage.
Capture incident context, document findings, track corrective actions, and implement improvements that prevent recurrence Review code and technical designs, document significant decisions and shared components, and help colleagues adopt and maintain the systems you own
What You’ll Bring
4+ years of software engineering experience for cloud-based products, including delivering changes to production and diagnosing problems in running services Practical experience delivering software with AI coding agents: breaking down work, providing context and constraints, guiding implementation, reviewing changes, and verifying behavior through tests and production telemetry Ability to explain, debug, and modify production code in at least one backend language, such as Go, TypeScript/Node.js, C#, or Java.
You must be able to recognize incorrect or incomplete generated code and take responsibility for the final implementation Experience designing or operating distributed systems, with an understanding of timeouts, retries, dependency failures, and recovery behavior Hands‑on experience with Kubernetes, infrastructure as code using Terraform, and automated build, test, and deployment pipelines.
Experience with one CI/CD platform is sufficient; examples include GitHub Actions, GitLab CI, and Argo CD Experience using metrics, logs, and traces to investigate service behavior and using SLOs or error budgets to guide engineering decisions Ability to independently deliver an agreed improvement, communicate trade‑offs, coordinate dependencies, and identify when a decision needs broader architectural input Ability to participate in the regional on‑call coverage arrangements
Bonus Skills
Experience building reusable reliability tools adopted by other engineering teams Experience with Azure networking, cross‑region failover, DNS, gateways, or service meshes Experience with load testing and performance regression detection Experience reducing cloud costs and understanding their contribution to cost of goods sold (COGS). Ability to evaluate cost implications during architecture and capacity planning, including cross‑region data transfer costs, while balancing reliability and performance Experience incorporating security and compliance requirements into software and delivery automation
What You’ll Get
25 vacation days, 4 sick days, 21 paid medical leave days, plus 4 extra global VeeaMe Days for self‑care and 24 paid volunteer hours annually through Veeam Cares Premium private medical insurance for employees and dependents Daily meal vouchers for restaurants and groceries (180 CZK per working day) Flexible cafeteria platform with thousands of lifestyle benefit options Multisport Card for gym and wellness, with family add‑on options Annual public transport reimbursement up to a set limit Corporate mobile plan with optional family tariff Opportunities to learn and grow through on‑demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops and learning events like our annual Global Day of Learning