Senior Infrastructure Engineer

As a Senior Infrastructure Engineer at Gradial, you will architect and evolve the systems that power our AI-driven content operations platform. This role is ideal for someone who thrives in startup-to-scale up environments and brings a deep understanding of how to make infrastructure reliable, secure, and scalable.

You’ll play a critical role in building on our core systems, supporting rapid product iteration and ensuring the platform is built for growth. If you’ve owned infrastructure in production, guided system evolution, and want to shape the future AI, we’d love to meet you.

• Design and maintain scalable, secure, and resilient infrastructure to support Gradial’s AI platform.
• Lead Kubernetes cluster management, CI/CD pipelines, observability tooling, and infrastructure-as-code efforts.
• Anticipate scaling needs and proactively evolve infrastructure architecture to support growth and reliability.
• Take full ownership of real-time, compute-intensive services: designing, deploying and maintaining to meet high performance standards with minimal oversight.
• Establish and enforce best practices for system reliability, performance monitoring, and disaster recovery.
• Evaluate and implement infrastructure automation tools to improve deployment velocity and reduce operational burden.
• Act as a strategic voice on infrastructure investment, technical debt management, and long-term scalability planning.

• 5+ years of experience in DevOps, SRE or platform engineering roles.
• Proven track record designing and operating large-scale, production-grade infrastructure.
• Deep expertise in Kubernetes, cloud-native architecture, and container orchestration.
• Proficiency with infrastructure-as-code (e.g., Terraform, GitOps ), CI/CD tooling, and monitoring stacks (e.g., Prometheus, Grafana).
• Experience in high-growth environments, especially scaling infrastructure from early product-market fit to maturity.
• Strong communication skills and a collaborative, ownership-driven mindset.

• Familiarity with AI/ML infrastructure, including GPU provisioning and model deployment.
• Prior experience supporting cloud or multi-cloud architectures.
• Comfort with TypeScript or Python to support tooling and operational scripts.

• Learn quickly, actively seek out new challenges, and regularly reconsider “how it’s always been done.”
• Have an innate drive for being 1% better than the day before, building towards greatness.
• Embrace AI as a core tool for problem-solving, innovation, and scale.
• Show customer-obsession (internal or external), high ownership/accountability, and bias for action.
• Communicate clearly, directly, with curiosity, and assuming good intentions.
• Thrive in fast-paced, hyper-growth environments where building better > maintaining status quo.

As an AI-first company, we prioritize AI literacy as a core competency in our hiring decisions. We’re excited by candidates who thoughtfully apply AI tools in their work, but during interviews we’re focused on you. This is your opportunity to show how you think, communicate, and solve problems. Over-reliance on AI-generated responses during the interview process (especially when it obscures your own voice) will result in disqualification. We want to understand your unique perspective and how you approach challenges, both with and without AI.

Gradial is dedicated to creating an environment where diverse perspectives are valued and all team members can grow. We offer competitive compensation, equity, flexible work hours, comprehensive benefits, and a collaborative culture focused on learning and impact.