Overview
FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build ris
Full job description
FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
We are looking for an experienced infrastructure engineer to help build and operate the internal platform systems that power engineering and production workloads across the company. This role focuses on Kubernetes infrastructure, deployment automation, cloud platform engineering, observability, and production reliability. You’ll work closely with software engineering teams to improve developer experience, deployment velocity, and operational scalability across the organization.
Design, deploy, and operate cloud infrastructure on AWS using infrastructure-as-code tooling such as AWS CDK and Terraform
Build and maintain Kubernetes platforms and supporting infrastructure across cloud and internal environments
Develop and improve CI/CD systems, deployment workflows, and GitOps tooling using GitHub Actions and ArgoCD
Improve reliability, scalability, observability, and operational maturity across distributed systems and data pipelines
Debug and resolve production issues spanning application, infrastructure, networking, and deployment layers
Partner with engineering teams to improve developer productivity, deployment velocity, and operational efficiency
Implement monitoring, alerting, autoscaling, and incident response best practices for production systems
Help define infrastructure standards, deployment patterns, and operational best practices as systems evolve
10+ years of experience in infrastructure engineering, platform engineering, production engineering, or DevOps-focused software engineering roles
Strong hands-on Kubernetes experience operating production systems at scale
Deep experience with AWS infrastructure, including networking, IAM, compute, storage, and observability services
Experience with infrastructure-as-code tooling such as Terraform, AWS CDK, or CloudFormation
Strong programming skills in Python, Go, TypeScript, or similar languages
Experience designing and operating distributed systems and event-driven architectures
Strong debugging and incident response skills across infrastructure and application layers
Experience building CI/CD systems and deployment automation pipelines
Ability to work cross-functionally and take ownership of systems end-to-end
Experience with GitOps workflows and tools such as ArgoCD
Experience with observability tooling such as Prometheus, Grafana, OpenTelemetry, or Datadog
Experience operating Kafka, PostgreSQL, Redis, or other distributed data systems
Experience with autoscaling systems such as KEDA
Experience building internal developer platforms or shared engineering infrastructure
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