AI Platform Engineer - Kubernetes & Multi-Cloud Infra

Intapp; United States; On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Free lunches

Fully stocked kitchens

Professional development reimbursement

Flexible time off

Volunteer time off and donation-mating

Job summary

Intapp is seeking a Platform/DevOps engineer to operate and evolve a Kubernetes-based AI workload platform, integrating cloud models across providers and delivering IaC and GitOps workflows. You will build observability, incident response, and self-hosted model serving with GPU workloads, while hardening security and access controls.

You will collaborate with internal product teams, document processes, and help troubleshoot in a fast-paced, modern environment.

Qualifications

• 3+ years in platform, DevOps, SRE, or cloud engineering.
• Hands-on Kubernetes deployments, networking, and troubleshooting.
• Terraform and GitOps tooling experience.
• Experience with at least one major cloud (Azure or AWS).
• Observability tools knowledge and scripting ability.

Responsibilities

• Operate and evolve a Kubernetes-based platform for AI workloads and gateways.
• Integrate and manage access to cloud-hosted foundation models across providers.
• Deliver infrastructure as code and GitOps workflows.
• Build monitoring, alerting, and tracing for AI workloads.
• Design self-hosted model serving including GPU workloads.
• Harden platform with secrets, policies, auth, and audit logging.
• Support internal teams with documentation, onboarding, and troubleshooting.

Skills

Cloud platform engineering

SRE practices

CI/CD mindset

Tools

Kubernetes

Terraform

GitOps (Argo CD/Flux)

Azure/AWS

Observability stack (OpenTelemetry/Prometheus/Grafana)

Python/Go/Bash

Job description

Intapp is seeking a Platform/DevOps engineer to operate and evolve a Kubernetes-based AI workload platform, integrating cloud models across providers and delivering IaC and GitOps workflows. You will build observability, incident response, and self-hosted model serving with GPU workloads, while hardening security and access controls.

You will collaborate with internal product teams, document processes, and help troubleshoot in a fast-paced, modern environment.