Senior Software Engineer, AI Platform

Procore Technologies•Austin, TX

19h•Hybrid

About The Position

Procore Technologies is seeking a senior engineer to ensure the infrastructure powering its AI agents remains high-performing, resilient, and cost-efficient as customer adoption grows. The role works closely with application engineers, data scientists, and platform teams to build multi-cloud deployment pipelines, scale vector databases, and optimize a multi-provider LLM gateway. It is based in the Austin, Texas office and is hybrid, with two days per week in the office. The position reports to the VP of Engineering.

Requirements

At least 5 years of experience building and operating production infrastructure at scale.
Hands-on expertise with Google Cloud, including GKE, Vertex AI, IAM, VPC networking, BigQuery, and Cloud Monitoring.
Production experience with AWS, including EKS, Lambda, IAM, RDS/Aurora, and SQS/SNS, and infrastructure management with Terraform across multi-cloud environments.
Production Kubernetes expertise, including autoscaling, resource tuning, cluster lifecycle management, Helm, and GitOps workflows such as Argo CD or equivalent.
Practical experience running LLMs in production through provider APIs, including quota management, load balancing, and multi-provider routing.
Experience deploying and operating distributed vector databases, search engines, and stateful data stores on Kubernetes.
Strong background in observability design, including alert policies, SLOs, Datadog dashboards, and incident response runbooks.
Track record of measurable performance and cost optimizations across cloud architectures, with the ability to articulate engineering trade-offs.
Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.

Nice To Haves

Background as a Senior MLOps Engineer or AI Platform Engineer.
Background as a Senior Cloud Infrastructure Engineer with GCP and AWS experience.
Background as a Senior Site Reliability Engineer specializing in Kubernetes and stateful distributed systems.
Background as a Platform or Developer Experience Engineer focused on AI/ML enablement.

Responsibilities

Operate, scale, and maintain production workloads across Google Cloud and AWS to provide a resilient, unified multi-cloud foundation for Procore's AI agent portfolio.
Manage production AI model workloads across Vertex AI, Amazon Bedrock, and Anthropic, including provider fallback, regional availability routing, and GPU-backed self-hosted model serving on Kubernetes.
Optimize GKE and EKS clusters through resource requests, limits, and dynamic autoscaling.
Plan capacity and right-size stateful backends, queues, BigQuery storage, and vector databases using workload patterns and growth forecasts.
Lead lifecycle management, staged rollouts, upgrades, and automated rollback strategies for production databases and search infrastructure.
Establish service-level objectives, automated alerting, distributed agent tracing, and Datadog monitoring that reflect user experience and reduce operational noise.
Build secure CI/CD pipelines, reproducible staging environments, and developer tooling to accelerate delivery and support application engineers building on the AI platform.