📍 Job Overview

Job Title: Senior Software Engineer - Kubernetes and Infrastructure
Company: Cast AI
Location: Budapest, Central Hungary, Hungary
Job Type: Full-Time
Category: DevOps Engineer, System Administrator
Date Posted: 2025-02-20
Experience Level: Mid-Senior Level (5-10 years)
Remote Status: Remote (GMT 0 – GMT +3)

🚀 Role Summary

📝 Enhancement Note: This role involves designing, building, and operating backend services and Kubernetes operators to manage clusters across major cloud providers. It requires a strong understanding of Kubernetes internals, cloud infrastructure, and distributed systems.
Cast AI is seeking a Senior Software Engineer to contribute to the low-level guts of Kubernetes, focusing on controllers, operators, networking, scheduling, and cloud provider low-level services for infrastructure resources. The ideal candidate will also work on APIs and tooling that make these capabilities effortless for thousands of engineers worldwide.

💻 Primary Responsibilities

📝 Enhancement Note: The primary responsibilities revolve around designing, building, and maintaining backend services and Kubernetes operators in Go. The role also involves extending and maintaining Terraform providers and other IaC components, contributing to high-volume data-plane services, and shaping public and internal APIs.
Design, build, and operate backend services and Kubernetes operators in Go that manage clusters across AWS, GCP, and Azure.
Develop cluster networking, scheduling, and orchestration features that unlock seamless workload portability and resource efficiency.
Extend and maintain the Terraform provider and other IaC components that integrate CAST AI with customer environments.
Contribute to high-volume data-plane services (gRPC/REST) and asynchronous workflows.
Shape public and internal APIs with an eye for simplicity and developer experience.
Participate in design reviews, code reviews, on-call rotations, and occasional customer deep-dives.

🎓 Skills & Qualifications

Education: A Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may substitute for a degree.

Experience: Proven experience (5-10 years) in backend engineering, preferably with a focus on Kubernetes, cloud infrastructure, or large-scale distributed systems.

Required Skills:

Proficiency in Go and experience with Kubernetes internals.
Strong background in cloud infrastructure (AWS, GCP, Azure) and distributed systems.
Familiarity with Kubernetes controllers, operators, networking, and scheduling.
Experience with Terraform and other IaC components.
Knowledge of gRPC, REST, and asynchronous workflows.
Understanding of API design and developer experience.

Preferred Skills:

Contributions to the Kubernetes or cloud native OSS ecosystem.
Deep knowledge of cloud networking, storage, or virtualization.
In-depth understanding of EKS, GKE, or AKS architecture and operations.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate your experience with Kubernetes, cloud infrastructure, and backend services through relevant projects and case studies.
Showcase your proficiency in Go by including code samples or open-source projects.
Highlight your API design and development skills with examples of public and internal APIs you've worked on.
Demonstrate your experience with Terraform and other IaC components through relevant projects.

Technical Documentation:

Detailed documentation of your projects, including code comments, version control, deployment processes, and server configuration.
Explanations of your problem-solving approach and architecture decisions for your projects.
Performance metrics and optimization techniques used in your projects.

💵 Compensation & Benefits

Salary Range: €6,500 – €9,000 per month (gross), depending on experience.

Benefits:

Competitive compensation and equity options.
Hardware budget and professional development stipend.
Flexible, remote-first work culture with occasional team events or conferences.
Iterative development process with feature projects typically shipping in 1-4 weeks.
10% innovation time to invest in learning or side projects.

Working Hours: 40 hours per week, with flexible scheduling to accommodate deployment windows and maintenance tasks.

🎯 Team & Company Context

Company Culture:

Industry: Cast AI is the leading Application Performance Automation (APA) platform, enabling customers to cut cloud costs, improve performance, and boost productivity – automatically.
Company Size: Medium-sized company with a remote-first culture and a global presence in over 32 countries.
Founded: 2018, with headquarters in Miami, Florida.

Team Structure:

The team works on the low-level guts of Kubernetes, focusing on controllers, operators, networking, scheduling, and cloud provider low-level services for infrastructure resources.
The team is responsible for designing, building, and operating backend services and Kubernetes operators, as well as extending and maintaining Terraform providers and other IaC components.
The team collaborates with other departments, such as customer success and product management, to ensure customer needs are met and the platform evolves accordingly.

Development Methodology:

Agile/Scrum methodologies are used for sprint planning and development processes.
Code review and testing are integral parts of the development process to ensure code quality and performance.
CI/CD pipelines are employed for automated deployment and server management.

Company Website: castai.com

📝 Enhancement Note: Cast AI values customer obsession, leading through action, developing and hiring the best, and expecting and advocating change. These core values guide the company's culture and team dynamics.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior level, focusing on backend engineering, Kubernetes, and cloud infrastructure. It requires a deep understanding of these technologies and the ability to lead projects and mentor junior team members.

Reporting Structure: The Senior Software Engineer will report directly to the Engineering Manager and work closely with other engineers, product managers, and customer success teams.

Technical Impact: The role involves designing, building, and operating backend services and Kubernetes operators that manage clusters across major cloud providers. This has a significant impact on the platform's performance, scalability, and user experience.

Growth Opportunities:

Technical leadership and architecture decision-making opportunities as the platform and team grow.
Innovation time (10%) to invest in learning new technologies, contributing to open-source projects, or working on side projects.
Career progression paths within the engineering organization, such as becoming a Tech Lead or Engineering Manager.

📝 Enhancement Note: Cast AI's remote-first culture and global presence offer opportunities for career growth and exposure to diverse teams and technologies.

🌐 Work Environment

Office Type: Remote-first work environment with occasional team events or conferences.

Office Location(s): Cast AI has employees in over 32 countries worldwide, with a strong presence in the GMT 0 – GMT +3 time zone.

Workspace Context:

Remote work with flexible scheduling to accommodate deployment windows and maintenance tasks.
Collaborative development environment with regular design reviews, code reviews, and on-call rotations.
Cross-functional collaboration with customer success, product management, and other departments to ensure customer needs are met and the platform evolves accordingly.

Work Schedule: 40 hours per week, with flexible scheduling to accommodate deployment windows and maintenance tasks.

📝 Enhancement Note: Cast AI's remote-first culture and global presence offer a flexible work environment that prioritizes results and collaboration over physical presence.

📄 Application & Technical Interview Process

Interview Process:

Technical preparation for coding and configuration assessment, focusing on Kubernetes, cloud infrastructure, and backend services.
Web architecture expectations and system design discussion, focusing on cluster networking, scheduling, and orchestration features.
Web development team interaction and cultural fit assessment, focusing on Cast AI's core values and team dynamics.
Final evaluation criteria and technical impact discussion, focusing on the candidate's ability to lead projects and mentor junior team members.

Portfolio Review Tips:

Demonstrate your experience with Kubernetes, cloud infrastructure, and backend services through relevant projects and case studies.
Showcase your proficiency in Go by including code samples or open-source projects.
Highlight your API design and development skills with examples of public and internal APIs you've worked on.
Demonstrate your experience with Terraform and other IaC components through relevant projects.

Technical Challenge Preparation:

Practice Kubernetes and cloud infrastructure exercises to prepare for the technical assessment.
Review Cast AI's core values and be prepared to discuss how you embody them in your work.
Prepare for system design discussions by practicing architecture decision-making and trade-off analysis.

ATS Keywords:

Programming Languages: Go, Python, Bash, SQL
Web Frameworks: Kubernetes, Terraform, Temporal
Server Technologies: AWS, GCP, Azure, EKS, GKE, AKS
Databases: PostgreSQL
Tools: Git, GitLab CI, GitHub CI, Argo CD, Prometheus, Grafana, Loki, Tempo
Methodologies: Agile, Scrum, CI/CD, GitOps
Soft Skills: Communication, Collaboration, Problem-Solving, Leadership, Mentoring
Industry Terms: Kubernetes, Cloud Infrastructure, Backend Services, API Design, IaC, DevOps, MLOps

📝 Enhancement Note: Familiarize yourself with Cast AI's core values, team structure, and development methodology to succeed in the interview process.

🛠 Technology Stack & Web Infrastructure

Backend & Server Technologies:

Go for backend services and Kubernetes operators.
Kubernetes controllers, operators, networking, and scheduling for managing clusters across major cloud providers.
AWS, GCP, and Azure for cloud infrastructure and resource management.
Terraform and other IaC components for integrating CAST AI with customer environments.

Development & DevOps Tools:

Git for version control and collaborative development.
GitLab CI, GitHub CI, and Argo CD for CI/CD pipelines and automated deployment.
Prometheus, Grafana, Loki, and Tempo for web performance tracking and server monitoring.

📝 Enhancement Note: Cast AI's technology stack is designed to be flexible and adaptable, allowing engineers to work on various components of the platform and infrastructure.

👥 Team Culture & Values

Web Development Values:

Practice Customer Obsession by focusing on the customer journey and delivering customer value.
Lead through action and think and act on behalf of the whole company to build long-term value across team boundaries.
Develop and Hire the Best by continuously investing in personal development, professional growth, and hiring the best possible candidates for every position.
Expect and Advocate Change by welcoming new ideas and opinions, sharing insights responsibly, and committing to a direction once a path is chosen.

Collaboration Style:

Cross-functional integration between developers, customer success, product management, and other departments.
Code review culture and peer programming practices to ensure code quality and performance.
Knowledge sharing, technical mentoring, and continuous learning to raise the collective bar and drive personal development.

📝 Enhancement Note: Cast AI's core values guide the team's culture and dynamics, fostering a collaborative and customer-focused work environment.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Modernizing Kubernetes and ensuring seamless workload portability and resource efficiency across major cloud providers.
Optimizing performance and scalability for high-volume data-plane services and asynchronous workflows.
Extending and maintaining Terraform providers and other IaC components to integrate CAST AI with customer environments.
Designing and implementing public and internal APIs with an eye for simplicity and developer experience.

Learning & Development Opportunities:

Technical skill development in Go, Kubernetes, cloud infrastructure, and emerging technologies.
Conference attendance, certification, and community involvement to stay up-to-date with industry trends and best practices.
Technical mentorship, leadership development, and architecture decision-making opportunities as the platform and team grow.

📝 Enhancement Note: Cast AI's remote-first culture and global presence offer opportunities for career growth and exposure to diverse teams and technologies.

💡 Interview Preparation

Technical Questions:

Kubernetes and cloud infrastructure fundamentals with a focus on controllers, operators, networking, and scheduling.
API design and development with an emphasis on simplicity, developer experience, and performance optimization.
System design and architecture decision-making with a focus on trade-off analysis and scalability.

Company & Culture Questions:

Cast AI's core values and how they guide the team's culture and dynamics.
Agile/Scrum methodologies and their application in Cast AI's development process.
Customer success and product management collaboration to ensure customer needs are met and the platform evolves accordingly.

Portfolio Presentation Strategy:

Demonstrate your experience with Kubernetes, cloud infrastructure, and backend services through relevant projects and case studies.
Showcase your proficiency in Go by including code samples or open-source projects.
Highlight your API design and development skills with examples of public and internal APIs you've worked on.
Demonstrate your experience with Terraform and other IaC components through relevant projects.

📝 Enhancement Note: Prepare for technical and cultural fit assessments by familiarizing yourself with Cast AI's core values, team structure, and development methodology.

📌 Application Steps

To apply for this Senior Software Engineer - Kubernetes and Infrastructure position:

Customize your resume to highlight your relevant experience with Kubernetes, cloud infrastructure, and backend services.
Tailor your portfolio to showcase your proficiency in Go, API design, and Terraform, with a focus on Cast AI's technology stack and requirements.
Prepare for the technical interview by practicing Kubernetes and cloud infrastructure exercises, reviewing Cast AI's core values, and preparing for system design discussions.
Research Cast AI's company culture and be prepared to discuss how you embody their core values in your work.