DevSecOps Engineer
- Raya
- Remote USA
Job Description
We prioritize learning and teamwork and love giving people the opportunity to champion solutions to big challenges and grow into better versions of themselves. A great candidate believes in Raya's vision, which is to enrich lives by fostering relationships through quality, in person interactions.
You thrive at the intersection of DevOps and Security, and you're excited to drive measurable impact by hardening our AWS/EKS environment and systematically closing out security findings.
Responsibilities
Qualifications
Strong hands-on experience with AWS and Kubernetes/EKS, comfortable navigating cloud infrastructure and container environments from day one
Solid foundation in security fundamentals: vulnerability management, IAM, network security, and cloud security posture management
Experience triaging and remediating security findings from vulnerability scanners or cloud security tools
Familiarity with CI/CD pipelines and integrating security practices into the software development lifecycle
Strong communication skills, able to work effectively with both DevOps and Security stakeholders and translate technical risk into clear priorities
Experience with Infrastructure-as-Code (e.g., Terraform/OpenTofu), compliance frameworks, or container security tooling
What Set's You Apart
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Bridge Builder: You naturally sit at the intersection of DevOps and Security, translating between the two and earning trust from both sides
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Impact-driven: You prioritize the fixes and improvements that meaningfully reduce risk, rather than chasing every alert
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Growth-oriented: You possess a perpetual learner's mindset, staying curious about new threats, tools, and cloud-native security practices
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Ownership mentality: You take findings from discovery to resolution without needing to be chased, and you build systems so problems don't recur
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Productivity-obsessed: You value tools, workflows, and automation that make security scalable rather than manual
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Bias toward shipping and iteration: You're able to harden systems incrementally, learn, and refine in short cycles rather than waiting for a "perfect" fix
