Cloud Platform Engineer
About The Position
Operate and evolve a Kubernetes-based platform for AI workloads, including LLM gateways, agent and tool-integration gateways, and agent runtimes. Integrate and manage access to cloud-hosted foundation models across multiple providers, covering routing, quotas, fallbacks, cost controls, and tenant isolation. Deliver infrastructure as code and GitOps workflows, and build monitoring, alerting, and tracing for AI workloads. Help design and prototype self-hosted model serving, including GPU workloads and inference runtimes. Harden the platform through secrets management, network policies, authentication and authorization, and audit logging. Support internal product teams with documentation, onboarding, and troubleshooting. At Intapp, the role offers the opportunity to contribute to a growing public company in a modern work environment described as connected yet flexible. The company emphasizes collaboration, professional growth, well-being, creativity, innovation, and teamwork.
Requirements
- At least 3 years in platform, DevOps, SRE, or cloud engineering.
- Hands-on experience with Kubernetes, including deployments, networking, and troubleshooting.
- Experience with infrastructure as code (Terraform) and GitOps tooling (Argo CD, Flux, or similar).
- Solid experience with at least one major cloud, Azure or AWS.
- Experience with observability tools such as OpenTelemetry, Prometheus, and Grafana.
- Scripting and coding skills in Python, Go, or Bash, and CI/CD experience.
Nice To Haves
- Experience with LLM gateways or proxies, or LLM observability and tracing tools.
- Familiarity with managed model services from major cloud providers, such as Azure or AWS.
- Understanding of agent frameworks and tool-integration protocols such as Model Context Protocol (MCP).
- Experience running GPU workloads or model inference serving.
- Experience in multi-tenant, regulated, or compliance-driven environments.
Responsibilities
- Operate and evolve a Kubernetes-based platform for AI workloads, including LLM gateways, agent and tool-integration gateways, and agent runtimes.
- Integrate and manage access to cloud-hosted foundation models across multiple providers, including routing, quotas, fallbacks, cost controls, and tenant isolation.
- Deliver infrastructure as code and GitOps workflows.
- Build monitoring, alerting, and tracing for AI workloads.
- Help design and prototype self-hosted model serving, including GPU workloads and inference runtimes.
- Harden the platform with secrets management, network policies, authentication and authorization, and audit logging.
- Support internal product teams through documentation, onboarding, and troubleshooting.
Benefits
- Reimbursement for training and continuing education.
- Modern, open offices designed to support creativity and collaboration.
- Complimentary lunches and fully stocked kitchens.
- Wellness programs and flexible time off.
- Benefits designed to care for employees and their families.
- Family-formation benefits and support during the family-building journey.
- Paid volunteer time off.
- Donation matching program.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
