Secure Build, Release & Observability Engineer (DevOps Engineer) (m/f/d)

Pracovné podmienky

• Remote work
• full-time

Odmeňovanie

From 2 100 EUR/month

Final salary is negotiable.

We are offering base salary depending on seniority level and previous experience of candidate. In addition to base salary we provide variable part and other financial benefits.

Establish and operate the build, release, and observability backbone required for technical due diligence, code quarantine, reproducible software validation, controlled deployment preparation, and reliable engineering handover across cloud platform components

Role focus

This infrastructure and operations role focuses on CI/CD pipelines, artefact flows, release evidence, build reproducibility, observability, and operational controls. The candidate should make complex engineering environments measurable, supportable, and auditable while enabling AI-assisted code validation and documentation workflows.

Náplň práce

• Design and operate CI/CD pipelines for repository intake, build execution, image creation, artefact promotion, environment deployment, and evidence generation
• Implement release controls for private registries, package sources, signing, SBOM generation, vulnerability scanning, dependency provenance, and approval workflows
• Create observability across build systems, workflow services, repositories, test environments, model endpoints, and platform components using logs, metrics, traces, and dashboards
• Support troubleshooting of build failures, flaky pipelines, missing dependencies, environment drift, performance bottlenecks, and handover-readiness gaps
• Partner with software, SRE, testing, and security teams to define runbooks, operational KPIs, risk indicators, and audit-ready evidence packs for release decisions

Technológie a oblasti

• CI/CD and release tools, containerisation, orchestration, artefact management, and deployment automation
• Security and supply-chain tooling, including vulnerability scanning, SBOM workflows, dependency scanning, secrets detection, and policy gates
• Observability stacks using logs, metrics, traces, dashboards, log aggregation, and automated health checks
• AI engineering integrations such as code-scanning workflows, model-backed log analysis helpers, documentation generators, internal model gateways, and workflow execution services
• Infrastructure automation using configuration management, scripting, GitOps patterns, private networks, controlled proxies, package mirrors, and secure secrets management