Senior Go & Kubernetes Distributed Systems Engineer Remote

Cast AI; United States; Remote; USD 81,000 - 112,000; Full time

Job summary

Cast AI in a remote-first setup seeks experienced engineers to design and implement distributed systems managing Kubernetes clusters at scale. You will develop production Go services that interact with AWS, GCP, and Azure APIs for real-time resource management, owning features end-to-end from design to production rollout in tight cycles.

The role emphasizes strong Go, Kubernetes internals, observability, and a startup mindset, with collaboration across teams and on-call rotation as needed.

Qualifications

• Strong software engineering fundamentals and clean abstractions.
• Production Go experience preferred; strong systems programming ok.
• Understanding of Kubernetes autoscaling and networking.
• English communication skills (verbal and written).
• Startup mindset: adaptable and proactive.

Responsibilities

• Design and build distributed systems operating Kubernetes autonomously at scale.
• Write production Go services interacting with cloud APIs for real-time management.
• Own features end-to-end from design to production rollout (1–4 weeks).
• Debug production issues across clouds, clusters, and services.
• Collaborate with product and other teams to solve novel problems.
• Work with time-series data and Kubernetes control plane internals.
• Participate in on-call rotation when required.

Skills

Go programming

Kubernetes internals

System design

CI/CD

Observability

DevOps practices

English proficiency

AI workflows

Startup mindset

Tools

AWS

GCP

Azure

Terraform

PostgreSQL

ClickHouse

gRPC

REST APIs

Prometheus

Grafana

Loki

Tempo

GitLab CI

ArgoCD

Kargo

Karpenter

Job description

Cast AI in a remote-first setup seeks experienced engineers to design and implement distributed systems managing Kubernetes clusters at scale. You will develop production Go services that interact with AWS, GCP, and Azure APIs for real-time resource management, owning features end-to-end from design to production rollout in tight cycles.

The role emphasizes strong Go, Kubernetes internals, observability, and a startup mindset, with collaboration across teams and on-call rotation as needed.