To succeed in the Wave interview process, you must demonstrate a balance of technical expertise, pragmatic problem-solving, and strong communication. The hiring team is not just looking for someone who can write scripts; they want an engineer who understands the "why" behind their technical choices.

Technical Rigor & Systems Thinking – You must show a deep understanding of cloud-native architectures, container orchestration, and modern infrastructure practices. Be prepared to explain how different components of a system interact, where potential bottlenecks lie, and how to build for high availability.

Troubleshooting Under Pressure – A core part of the evaluation is how you approach ambiguous, complex production issues. Interviewers will observe your diagnostic methodology. You should demonstrate a structured, logical approach to isolating variables and identifying root causes rather than guessing at solutions.

Pragmatic Execution – Wave values engineers who deliver practical, maintainable solutions over over-engineered systems. When presenting designs or completing assignments, explain the trade-offs you made, why you chose a specific tool or pattern, and how you would iterate on the solution over time.

Collaboration & Cultural Alignment – DevOps at Wave is a collaborative discipline. You need to demonstrate that you can partner effectively with software development teams, communicate technical concepts clearly to non-technical stakeholders, and receive constructive feedback with an open mind.

The interview process at Wave is structured to evaluate your practical engineering capabilities, your architectural thinking, and your cultural alignment with the team. The process is thorough and highly technical, but it is designed to mimic real-world engineering challenges rather than abstract academic puzzles.

You will begin with an initial screening call with a recruiter to discuss your background, career goals, and alignment with the role. Following a successful screen, you will receive a practical take-home assignment that simulates real production challenges. This is followed by deep-dive technical rounds focusing on your assignment, live troubleshooting scenarios, and discussions with engineering leadership about your past experiences and architectural philosophy.

The timeline above outlines the typical progression of a candidate through the hiring pipeline. You should use this sequence to pace your preparation, focusing first on practical implementation skills for the take-home task, and then shifting toward system design, live troubleshooting, and behavioral scenarios for the subsequent rounds. While the exact duration can vary based on candidate availability and team scheduling, the core stages remain consistent.

Take-Home Assignment & Code Review

The take-home assignment is a critical component of the Wave hiring process. It is designed to evaluate your practical, hands-on engineering skills in a realistic scenario, such as modifying application and Infrastructure as Code (IaaS) configurations to resolve issues within a simulated Kubernetes cluster.

Be ready to go over:

• Kubernetes Configuration – Structuring manifests, managing deployments, and configuring network policies or ingress controllers.
• Infrastructure as Code (IaaS) – Writing clean, modular Terraform or CloudFormation code that adheres to industry best practices.
• Application Integration – Modifying application code or configurations to ensure seamless integration with containerized environments.
• Adherence to Rubrics – Delivering a solution that strictly meets every requirement outlined in the provided instructions.

Example scenarios:

• Debugging a broken deployment in a local Kubernetes cluster where the application cannot connect to its database due to misconfigured secrets or network policies.
• Refactoring a monolithic deployment manifest into modular, reusable Terraform code while ensuring proper environment separation.

Systems Troubleshooting & Monitoring

This interactive session evaluates how you diagnose and resolve complex system failures under simulated production conditions. Rather than a passive Q&A, this is a collaborative, round-table discussion where you work through scenarios alongside Wave engineers.

Be ready to go over:

• Diagnostic Methodology – How you systematically isolate variables, analyze logs, and trace requests across a distributed system.
• Monitoring & Alerting Design – Defining key performance indicators (KPIs), setting up meaningful alerts, and avoiding alert fatigue.
• Incident Mitigation – Prioritizing rapid service restoration before deep-diving into long-term root-cause analysis.
• Advanced concepts (less common) – Distributed tracing implementation, service mesh configuration, and kernel-level performance tuning.

Example scenarios:

• A sudden spike in 502 Bad Gateway errors occurs on the main API gateway during peak hours. Walk through how you would isolate the issue.
• An application's response time degrades over several hours, but CPU and memory utilization on the host VMs remain low. How do you investigate?

Architectural Rationale & Culture Fit

In these final rounds, you will meet with engineering managers, senior leaders, and potentially the CTO. The focus shifts from daily tasks to long-term architectural vision, past project execution, and cultural alignment.

Be ready to go over:

• Past Project Deep Dives – Explaining the architecture of systems you have built, the challenges you faced, and what you would do differently today.
• Technical Trade-offs – Defending your design choices, such as choosing specific cloud services or deciding when to build versus buy.
• Collaboration & Mentorship – How you work with software developers to promote DevOps best practices and how you handle conflicting technical opinions.
• Cultural Values – Demonstrating curiosity, a growth mindset, and a commitment to operational excellence.

Example scenarios:

• Describing a situation where you had to influence a development team to adopt a new deployment tool or security practice that initially slowed down their workflow.
• Explaining how you designed an infrastructure migration plan to move a high-traffic service to a new cloud provider with zero downtime.

As a DevOps Engineer at Wave, your daily work will revolve around maintaining a highly resilient cloud platform while continuously improving the developer experience. You will be embedded within or closely aligned with engineering teams, ensuring that infrastructure considerations are integrated into the software development lifecycle from day one.

Your primary technical responsibility is the health and performance of Wave's production infrastructure. This includes managing multi-tenant Kubernetes clusters, optimizing cloud resources, and ensuring that continuous integration and continuous deployment (CI/CD) pipelines are fast, secure, and reliable. You will write and maintain the Infrastructure as Code (IaaS) that defines these environments, ensuring that infrastructure changes are version-controlled, peer-reviewed, and automatically deployed.

Beyond pure infrastructure management, you will act as a force multiplier for the entire engineering organization. You will collaborate with software engineers to design scalable application architectures, establish robust monitoring and alerting patterns, and participate in an on-call rotation to support production systems. By building intuitive internal tools and self-service platforms, you will enable development teams to provision resources, deploy code, and monitor their services independently and safely.