Senior Software Engineer, Cloud Platform

Evolve the ecosystem: Own the multi-quarter roadmap for our GCP and Kubernetes-based cloud capabilities, balancing developer feedback with emerging cloud technologies and building consensus among senior stakeholders.

Drive operational excellence: Set the standard for SLOs and incident management across the platform, and share ownership of platform health through on-call rotations — using those frontline insights to harden systems at scale.

Embed security: Architect access controls, encryption, and vulnerability management as a foundational platform standard that keeps the platform secure without slowing developer velocity.

Optimize footprint: Set the strategic direction for cloud capacity management and FinOps, delivering efficient scaling and cost transparency that other teams adopt as the standard.

Productize the platform: Own the technical strategy for turning CI/CD (GitHub Actions, TeamCity), deployment (ArgoCD), and build tooling into a cohesive, self-service product — driving Change Failure Rate toward zero across engineering.

Pave the golden path: Define the platform standards built directly into our tooling, so the right way is automatically the fastest and easiest way for every engineer at Signifyd.

Solve systemic problems: Serve as the escalation point for the most complex, ambiguous infrastructure challenges, delivering durable fixes and shaping how other teams approach similar problems.

Champion the culture: Foster a customer-focused engineering culture, mentor engineers at every level, raise the technical bar, and advocate for product-thinking and empathy for the developer experience.

Cloud Platform: Deep, demonstrated mastery of Google Cloud Platform (GCP); AWS experience is a strong plus. Expert-level knowledge of cloud networking, protocols, and security best practices, with a track record of setting standards others follow.

Kubernetes: Extensive expertise in architecting and operating self-managed and cloud-managed Kubernetes environments at scale, including setting Kubernetes strategy across multiple teams.

Data Systems: Proven experience in architecting and scaling data storage and streaming technologies (e.g., PostgreSQL, MySQL, Cassandra, Elasticsearch, Kafka) in ways that shape platform-wide standards.

Coding Proficiency: Strong software development skills in high-level languages (e.g., Python, Go, Java, TypeScript), with a history of setting engineering practices adopted beyond your immediate team.

IaC & GitOps: Demonstrated ability to architect secure, self-service infrastructure using Infrastructure-as-Code (Terraform) and declarative CI/CD pipelines (ArgoCD, GitHub Actions, TeamCity), driving down Change Failure Rate across teams.

AI Tooling: Proficiency with modern AI-assisted development tools (Cursor, GitHub Copilot, Claude), paired with the critical judgment to audit AI-generated code for security, correctness, and long-term maintainability — and to set guidelines for how teams adopt these tools responsibly.

Telemetry: Experience architecting scalable, OpenTelemetry-based monitoring and tracing that helps engineering teams quickly pinpoint bottlenecks and lower MTTR.

Architectural Mindset: Deep, cross-domain expertise in cloud security, cost optimization (FinOps), and performance efficiency, with a demonstrated ability to translate that expertise into technical strategy.

Execution: A track record of driving complex, cross-team technical initiatives to completion in a fast-paced, collaborative environment, with minimal oversight.

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