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.

• Embrace AI as a core tool for problem-solving, creativity and scale.
• Show a strong work ethic, high ownership and bias toward action.
• Communicate with clarity and curiosity.
• Thrive in fast-paced, hyper-growth environments; where building is always better than maintaining the 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.

By submitting your application to Gradial, you acknowledge that any personal data you provide will be processed in accordance with our Privacy Policy. This includes the collection, use, and storage of your information for the purposes of evaluating your qualifications and communicating with you about your candidacy. We handle applicant data with care and in compliance with applicable data protection laws.

If you have any questions about how your information is used, please refer to our Privacy Policy or contact us directly.

Applicants who require reasonable accommodation to participate in the application or interview process should contact us at careers@gradial.com to request assistance.