Cloud Platform Automation Engineer (f/m/d)
AI Summary
Designs and evolves secure AWS cloud foundations using infrastructure-as-code and automation, improves reliability and observability, leads incident response and resilience engineering, and mentors peers in a global platform engineering team.
About this role
Who is Sonar?
Sonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable.
Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code.
We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow, Booking.com, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like:
- SonarQube: The world’s leading AI code review and verification platform.
- SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.
- SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective.
Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE:
- Committed to our customers and community.
- Obsessed with quality.
- Deliberate in our decisions.
- Effective as one team.
With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you.
Position description
What you will do
Cloud platform engineering through code: Design and evolve secure, reliable AWS foundations using reusable infrastructure-as-code, automated deployment pipelines, and tested change controls.
Automation and self-service: Develop pragmatic tooling, integrations, and glue code that solve operational problems for Systems Engineering and make internal customers more self-sufficient.
AI-enabled platform engineering: Use and develop AI-enabled tooling and automation to improve infrastructure delivery, operational triage, knowledge retrieval, and self-service, with appropriate human review, security, and governance.
Reliability and observability: Define and improve monitoring, alerting, dashboards, runbooks, SLIs/SLOs, capacity planning, and service-health reporting for Systems Engineering services.
Security engineering: Design, architect, implement, and operate secure cloud controls — including least-privilege access, policy-as-code, secrets management, auditability, configuration baselines, and automated evidence collection — in partnership with Information Security.
Incident response: Participate in the Systems Engineering on-call and escalation model for services and tools owned by Systems Engineering. Lead or contribute to incident response, root-cause analysis, and preventative follow-up work.
Resilience engineering: Lead or facilitate FMEAs and recovery exercises for critical cloud services and material changes; translate findings into funded, owned engineering actions.
Technical leadership: Produce lightweight designs, establish standards, review complex changes, mentor peers, and influence service-owning teams to adopt reliable platform patterns.
Collaboration: Work closely with Systems Engineering, S/NOC, Information Security, IT Ops, Product Engineering, and external providers to define clean service boundaries and effective escalation paths.
Experience and qualifications
8+ years of hands-on experience in cloud, platform, site reliability, infrastructure, or DevOps engineering in a SaaS, cloud-native, or complex enterprise environment.
Strong AWS experience, including networking, IAM, DNS, logging/monitoring, compute, storage, security controls, and multi-account or multi-environment design.
Deep infrastructure-as-code experience with AWS CDK, Terraform, CloudFormation, or equivalent, including reusable modules, automated testing, code review, and CI/CD delivery.
Strong software engineering and automation skills in at least one of Python, TypeScript, Go, Bash, or a comparable language with a heavy emphasis on AI skillsets.
Experience designing production-grade observability: metrics, logs, traces, actionable alerting, dashboards, and operational runbooks.
Demonstrated ability to automate operational controls and remove manual work while preserving appropriate approvals, auditability, and safety.
Experience with incident response, post-incident engineering, root-cause analysis, and translating lessons into measurable reliability improvements.
Sound knowledge of cloud security principles: identity and access management, least privilege, encryption, secrets handling, secure networking, vulnerability management, and logging.
Excellent written and verbal English communication; able to explain technical decisions, risks, and trade-offs to both technical and non-technical stakeholders.
Skills
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