Staff Software Engineer, Cloud Platform

Signifyd helps merchants grow confidently by using technology to create frictionless shopping experiences and prevent fraud. The Staff Software Engineer I will set the technical vision for enterprise cloud infrastructure, drive scalable and secure platform engineering, and lead cross-team initiatives involving Kubernetes, cloud technologies, automation, AI, and machine learning.

Responsibilities:

• Define the architectural strategy for integrating LLM-powered, agentic tools across the platform. Set the technical direction for self-healing infrastructure and automated root-cause analysis, influencing multiple teams' roadmaps to cut operational toil and speed up incident resolution
• 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
• 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
• Architect access controls, encryption, and vulnerability management as a foundational platform standard that keeps the platform secure without slowing developer velocity
• Set the strategic direction for cloud capacity management and FinOps, delivering efficient scaling and cost transparency that other teams adopt as the standard
• 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
• 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
• Serve as the escalation point for the most complex, ambiguous infrastructure challenges, delivering durable fixes and shaping how other teams approach similar problems
• 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

Requirements:

• To ensure seamless system operations at scale, the ideal candidate will possess a strong software development skillset, exceptional analytical and communication skills, and deep technical proficiency across cloud technologies, containers, Kubernetes, cloud networking, security, and platform engineering
• Fluency in applying AI and machine learning to platform problems such as intelligent automation, anomaly detection, and AI-assisted developer tooling
• The knowledge of the infrastructure needed to run AI/ML workloads reliably at scale is a strong plus
• along with a demonstrated track record of driving initiatives that span multiple teams
• Deep, demonstrated mastery of Google Cloud Platform (GCP)
• Expert-level knowledge of cloud networking, protocols, and security best practices, with a track record of setting standards others follow
• Extensive expertise in architecting and operating self-managed and cloud-managed Kubernetes environments at scale, including setting Kubernetes strategy across multiple teams
• 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
• 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
• 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
• 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
• Experience architecting scalable, OpenTelemetry-based monitoring and tracing that helps engineering teams quickly pinpoint bottlenecks and lower MTTR
• Deep, cross-domain expertise in cloud security, cost optimization (FinOps), and performance efficiency, with a demonstrated ability to translate that expertise into technical strategy
• A track record of driving complex, cross-team technical initiatives to completion in a fast-paced, collaborative environment, with minimal oversight
• AWS experience is a strong plus