AI Infrastructure Engineer [Senior]

Description

The company builds multi-agent AI systems that automate complex business workflows on enterprise platforms such as SAP, Salesforce, Workday, Snowflake and DataBricks.

It is backed by Foundation Capital and led by a founding team.

The AI Infrastructure team builds and runs the base layer for the company's AI agents, so they run reliably, securely and consistently in every customer environment. That base is a portable cloud setup built on Kubernetes, networking and automation, so the product behaves the same on any cloud provider.

The role matters because it lets the company bring up and run enterprise customer environments under strict security and compliance rules without slowing developers. It lowers integration risk, standardizes operations across hyperscalers, and lets product teams ship safely.

Responsibilities

• Design and own production-grade AI agent infrastructure across several cloud providers, covering Kubernetes, Terraform, observability, security and reliability.
• Make architecture decisions with real ownership.
• Build and be the primary owner of the Azure or Oracle Cloud version of the cloud infrastructure, and support GCP and AWS as well.
• Make the infrastructure portable so it can be deployed into customer environments.
• Improve observability, security and system reliability.
• Deploy and run applications with Kubernetes and Terraform.
• Work closely with product and platform engineers to keep delivery moving.
• Design and build CI/CD pipelines, owning automated build, test and deployment for infrastructure and application code end to end.
• Build and maintain a reusable automation framework for daily DevOps and developer tasks: environment provisioning, secret rotation, dependency updates, compliance checks and release management.
• Automate runbooks and recurring operational work, find manual tasks across engineering and remove them with scripts, pipeline stages and self-service tools.
• Promote an automation-first approach: repeated work gets automated, and automated work gets monitored and maintained like production code.

Requirements

• 10-15+ years working in cloud infrastructure engineering.
• Hands-on depth in Terraform.
• Hands-on depth in Kubernetes.
• Hands-on depth in Azure, Oracle Cloud, GCP or AWS.
• A record of designing and owning CI/CD systems, including pipeline architecture, GitOps deployments, release automation and pipeline as code.
• Experience building DevOps and developer automation frameworks, using scripting in Bash, Python or similar, workflow orchestration and self-service tools that cut manual work.
• Solid networking fundamentals.
• Proven experience running real production systems.

Conditions

Nice to have: experience with FluxCD or other GitOps controllers, such as ArgoCD.

Nice to have: understanding of cloud security and DevSecOps, including security gates, SBOM generation and compliance checks in CI/CD.

Nice to have: a passion for clean, unified infrastructure and good practice.

Nice to have: software development and SDLC experience and a builder mindset.

Nice to have: eagerness to learn and a focus on robust, reliable infrastructure.

Nice to have: confidence owning and defending complex AI agent infrastructure decisions.

Nice to have: startup and/or big tech experience.

Nice to have: high self-motivation and a strong sense of ownership.

Nice to have: enjoyment of building foundational systems that other engineers depend on.

Senior individual contributor role, hands-on rather than managerial.

Benefits

• Work on advanced AI infrastructure with a real effect on enterprises.
• Own foundational systems at an early-stage, high-growth company.
• Work alongside a sharp, execution-focused founding team.
• Help shape how AI gets deployed on some of the largest enterprise platforms.