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Salary: USD 130,000 - 200,000 / annual
Gradial is an AI-native marketing operations platform that helps marketers and creatives move from idea to execution faster by orchestrating across martech stacks, workflows, and people. The company is Series B-backed and building software that adapts to users rather than forcing users to adapt.
As a Senior Infrastructure Engineer, you will architect and evolve the systems powering Gradial's AI-driven content operations platform. This role is ideal for someone who thrives in startup-to-scale-up environments and brings deep expertise in making infrastructure reliable, secure, and scalable.
Key responsibilities include:
- Design and maintain scalable, secure, and resilient infrastructure supporting the 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
Required qualifications:
- 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 (Terraform, GitOps), CI/CD tooling, and monitoring stacks (Prometheus, Grafana)
- Experience in high-growth environments, especially scaling infrastructure from early product-market fit to maturity
- Strong communication skills and collaborative, ownership-driven mindset
Nice-to-have skills:
- Familiarity with AI/ML infrastructure, including GPU provisioning and model deployment
- Prior experience supporting cloud or multi-cloud architectures
- Comfort with TypeScript or Python for tooling and operational scripts
The company values learning agility, continuous improvement, AI literacy, customer obsession, high ownership, clear communication, and thriving in fast-paced, hyper-growth environments.
