About the role
DevOps Automation Engineer
About the Role
Securin is an AI-native cybersecurity company. Our Preemptive Exposure Management Platform turns exposure data into clear decisions — giving organizations the confidence to know which risks are exploitable, what to fix first, and how to act before attackers do. We build with agents and verify with humans — treating AI as a genuine collaborator, holding agent-generated code to the same review standard as human-authored code, and shipping features only when test coverage and security checks are in place. We take end-to-end ownership, write maintainable code, and bring security awareness into every decision — not as a checkbox, but as a core discipline. The Role: A high-agency software engineer who uses coding agents as a force multiplier: generating design specs with AI, curating those outputs with engineering judgment, and shipping high-quality features at pace on the Securin cybersecurity platform. We're hiring a DevOps Automation Engineer to help Securin replace manual operational processes with AI-assisted, automated ones. The focus of this role goes beyond maintaining our existing pipelines: you'll look across our build, deploy, security, and infrastructure workflows to find the repetitive, human-in-the-loop work and systematically automate it. You'll work within our established DevOps stack — Terraform, Jenkins, SonarQube, and AWS — and use coding agents as a primary implementation tool. We're investing in AI-assisted development because it lets a small team deliver far more, and we're looking for someone who can take advantage of that leverage while maintaining full ownership of the quality of what ships. This role also serves as an important bridge to our India-based DevOps team. You'll partner with them regularly, align on shared standards and ownership, and help the two sides of the organization operate as one team. This is a hands-on senior individual contributor role with a clear mandate and real autonomy.
Responsibilities
• Feature Development: Design and ship full-stack features for the Securin platform end-to-end — using AI coding agents (Claude) to generate specs and boilerplate, then curating those outputs with engineering rigor, security context, and architectural judgment before finalizing.
• Global Collaboration: Work with teams in the US and India to facilitate communication, operations, and design. Required to attend 1-2 US evening meetings a week to sync with India based teams.
• Agent & Automation Engineering: Build agentic workflows and automation pipelines that streamline engineering — and enforce a human-in-the-loop review process ensuring every AI-produced change is critically evaluated for correctness, security, and fit before it reaches production.
• Platform & Infrastructure: Architect and maintain cloud-native SaaS services on AWS, contributing to API design, data modeling, and microservices architecture that power real-time threat intelligence ingestion and delivery.
• Security Mindset: Apply secure-by-design principles throughout development and work alongside Securin's security researchers to translate vulnerability intelligence domain knowledge into robust platform capabilities.
• AI Integration: Actively integrate GenAI tools into daily workflows - automating routine tasks, accelerating research and analysis, drafting documents, and building reusable AI-powered processes.
• Proactive Growth: Move beyond using GenAI to building with it - designing agent workflows, contributing reusable skills, and helping Securin compound its Proactive Exposure Management expertise.
• Identify manual, repetitive, or error-prone operational processes and replace them with automated, AI-assisted workflows — and measure the time and toil recovered.
• Build and maintain infrastructure as code in Terraform: modules, state strategy, environment promotion, drift detection, and remediation.
• Own and extend Jenkins pipelines across build, test, security scan, artifact, and deploy stages, including shared libraries and reusable pipeline patterns.
• Integrate and tune SonarQube quality gates so that code quality and security findings surface what matters without creating noise.
• Use coding agents (e.g. Claude Code) as a primary implementation vehicle — decomposing problems, defining specs and guardrails, directing the work, and reviewing the results thoroughly.
• Design and troubleshoot systems end to end across AWS, including compute, networking, IAM, storage, and how these services behave under failure.
• Investigate and resolve production and pipeline incidents, then capture what you learned in runbooks and automation so the same issue doesn't return.
• Partner with the India DevOps team on shared standards, on-call practices, and clear handoffs, including attending late-evening meetings a few times per week to maintain meaningful overlap with their working hours.
• Evaluate whether our current tooling is still the right fit, and where a change is warranted, plan and execute the migration methodically — treating our developers as the users of the platform and keeping them supported and productive throughout.
• Document what you build, so the automation you create is understandable and maintainable by the whole team.
Must Have
• Candidates must reside in or be within commuting distance to San Jose, CA or Albuquerque, NM.
• Candidates must be legally authorized to work in the United States without current or future employer sponsorship.
• Employment is contingent upon successful completion of a background check, including verification of prior employment.
• 3+ years building production SaaS
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.
• Public cloud experience required (AWS preferred, GCP or Azure acceptable)
• Deep familiarity with: Containerization, Serverless architecture, Event-driven architecture, RESTful API design
• Hands-on, daily use of AI coding agents is a prerequisite.
• Must be able to critically review agent-generated code and specs for: Hallucinations, Security flaws, Architectural drift before merging.
• Demonstrated ability to use GenAI tools (e.g., Claude, ChatGPT, etc.) for daily work - drafting, research, summarization, data analysis, code generation, or workflow automation as relevant to the role.
• Working knowledge of GenAI limitations including hallucination risk, context window constraints, and data sensitivity boundaries; ability to validate AI-generated output before acting on it.
• Familiarity with prompt engineering techniques - structuring multi-step instructions, providing context, and iterating on output quality to achieve production-grade results.
• Comfort with agentic AI workflows - using, designing, or building multi-step AI agents that execute tasks autonomously with human-in-the-loop validation.
• Awareness of AI security fundamentals - prompt injection risks, data classification rules, sandboxed execution, and responsible handling of sensitive data in AI workflows.
• Familiarity with connecting GenAI tools to internal data sources, APIs, and enterprise systems.
• Ability to contribute reusable AI skills, templates, agent configurations, or automation workflows to a shared repository for team-wide use.
• Willingness to learn and adopt new AI tools as they evolve; participation in AI adoption sprints, hackathons, and knowledge-sharing within the team.
• Applicants must be legally authorized to work in the United States and must not require current or future employment visa sponsorship.
• 2+ years of hands-on AWS experience across core services (EC2, ECS/EKS, S3, IAM, VPC, RDS, CloudWatch), including a practical understanding of how they behave under failure.
• Production experience with infrastructure as code, using any mainstream tool (Terraform, OpenTofu, Pulumi, CloudFormation/CDK, or similar) — you've designed and owned infrastructure definitions, not only worked within someone else's modules.
• Experience owning CI/CD pipelines in production, with any mainstream tooling (Jenkins, GitHub Actions, GitLab CI, CircleCI, Azure DevOps, or similar) — the concepts matter more to us than the specific product.
• Strong system design fundamentals: the ability to reason about tradeoffs, failure domains, state, idempotency, and blast radius before writing code.
• Strong system troubleshooting skills: a methodical, evidence-driven approach to debugging distributed systems and CI/CD pipelines, including under time pressure.
• Strong programming principles — software engineering discipline (testing, version control, modularity, code review, readable code) applied to infrastructure and tooling. Proficiency in Python, Go, or a comparable language.
• Experience using coding agents for substantive implementation work, along with the judgment to evaluate agent output critically and review it to the same standard as your own.
• Willingness to work with a distributed team across time zones, including late-evening meetings a few times per week with our India DevOps team.
• A developer-as-customer mindset: the judgment to weigh a tooling change on its merits, and the discipline to migrate in careful, well-communicated stages rather than disruptive cutovers.
• Clear written communication — much of your work will be documented for colleagues in other time zones.
Nice to Have
• AWS experience preferred over GCP or Azure.
• Direct experience with Terraform — this is what we use today, alongside Jenkins and SonarQube.
• Direct experience with Jenkins, including shared libraries and reusable pipeline patterns.
• Direct experience with SonarQube or comparable static analysis and code-quality gating (Snyk, Semgrep, Checkmarx, CodeQL).
• Containers and orchestration at production scale (Docker, Kubernetes/EKS).
• Observability tooling (CloudWatch, Datadog, Prometheus/Grafana, OpenTelemetry) and experience building alerting that teams trust.
• Security and compliance automation — secrets management, policy as code, SOC 2 or similar audit evidence collection.
• Experience building internal developer platforms or self-service tooling.
• Prior experience bridging onshore and offshore engineering teams.
• Background in security or vulnerability management products.
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