Senior Software Engineer | Kubernetes Automation | EU

castaigroupinc; United States; Remote; USD 80,000 - 111,000; Full time

Benefits offered by this job

Remote-first position

Equity options

Learning budget for conferences and课程

Hackathons

Equipment budget

Additional days off

Team-building budget

Job summary

castaigroupinc is hiring for a remote engineer to design and build distributed systems that autonomously run Kubernetes infrastructure at scale. You will deliver production services interfacing with AWS, GCP, and Azure to manage resources in real time.

The role emphasizes end-to-end ownership, strong Go or systems programming background, and a proactive startup mindset, with on-call rotations and cross-team collaboration.

Qualifications

• Strong software engineering fundamentals.
• Production Go experience preferred or depth in systems programming.
• Knowledge of Kubernetes internals, autoscaling & networking.
• Proven track record delivering complex end-to-end projects.
• Hands-on with AI coding agents and agentic development workflows.
• Familiar with observability tooling, CI/CD and DevOps practices.
• Excellent written and spoken English; startup mindset.

Responsibilities

• Design and build distributed systems that autonomously operate Kubernetes infrastructure at scale.
• Develop production services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.
• Own features end to end from design through implementation, testing, and production rollout, typically within 1–4 weeks.
• Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services.
• Collaborate with product and engineering peers on ambiguous problems, shaping backlog and direction.
• Participate in on-call rotation and work with time-series data and cloud provider APIs.

Skills

Go

Kubernetes

AI coding agents

CI/CD

Observability tooling

English

Job description

Role overview

Join a remote engineering team building autonomous infrastructure automation that runs Kubernetes and cloud-native environments at scale. The work centers on solving hard, continuous optimization problems: deciding which nodes to remove, which pods to relocate, and which storage volumes to resize, all in real time and without breaking live workloads. The role sits within several product groups that tackle node placement, autoscaler integrations, workload rightsizing, live pod migration, self-scaling storage, and GPU capacity across clouds.

Responsibilities

• Design and build distributed systems that autonomously operate Kubernetes infrastructure at scale.
• Develop production services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.
• Own features end to end, from design through implementation, testing, and production rollout, with most projects shipping in 1–4 weeks.
• Debug complex production issues spanning cloud providers, Kubernetes clusters, and distributed services.
• Collaborate with product and engineering peers on problems that lack textbook solutions, contributing to backlog shaping and product direction.
• Participate in on‑call rotation for teams that require it, working with time‑series data, cloud provider APIs, and Kubernetes control plane internals.

Requirements

• Strong software engineering fundamentals: ability to design clean abstractions, write maintainable code, and justify architectural choices.
• Production experience with Go is strongly preferred; candidates without Go should demonstrate comparable systems programming depth.
• Working knowledge of Kubernetes internals, particularly autoscaling and networking.
• A track record of personally driving a complex project end to end.
• Hands‑on experience with AI coding agents and agentic development workflows.
• Familiarity with observability tooling in production and CI/CD plus DevOps practices.
• Strong written and spoken English, plus an adaptable, proactive startup mindset comfortable with ambiguity.

Nice to have

• Deep experience with AWS, GCP, or Azure, including how compute, networking, and storage work under the hood.
• Detailed knowledge of EKS, GKE, or AKS internals.
• Container runtime exposure such as CRI‑O, runc, or containerd.
• Cloud storage depth covering block storage, CSI, volume management, and filesystem internals.
• Low‑level Linux experience with process internals, packet‑level networking (NAT, iptables, conntrack, eBPF, SDN), filesystems, and storage.
• Systems programming in C or C++, and contributions to Kubernetes or cloud‑native open source projects.

Benefits and work setup

• Remote‑first position; applications accepted from candidates in Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.
• Competitive gross salary in the €6,500–€9,000 range, depending on experience, plus equity options.
• Daily stack includes Go, Kubernetes, Terraform, PostgreSQL, ClickHouse, gRPC, Prometheus, Grafana, ArgoCD, and Kargo.
• Dedicated 10% timeforpersonal projectsorself‑improvement, an annual hackathon, and a learning budgetforconferencesandcourses.
• Equipment budget, team‑building budget, and additional days offtosupportwork‑lifebalance.
• Hiring process: recruiter screening, hiring manager interview, system design, live coding, and a culture check with an executive; a background check may run at the final stage.