To succeed in the Plangrid interview loop, you must demonstrate a balanced mix of systems thinking, coding proficiency, and collaborative skills. Your preparation should focus on showing not just what tools you know, but how you apply them to solve real-world engineering problems.

Role-Related Knowledge – You must show a deep, production-level understanding of cloud infrastructure, particularly AWS, and modern infrastructure-as-code practices using Terraform. Interviewers will evaluate your ability to write clean, modular, and reusable infrastructure code, as well as your familiarity with containerization and orchestration.

Problem-Solving & Coding – Plangrid expects its DevOps engineers to be software engineers first. You will be evaluated on your ability to write clean, runnable automation code, handle complex data structures, and approach algorithmic problems with an efficiency-first mindset.

System Design & Architecture – You should be prepared to design scalable, fault-tolerant cloud architectures. Interviewers look for your ability to identify single points of failure, make sensible trade-offs between consistency and availability, and design systems that scale horizontally.

Collaboration & Communication – Because you will support multiple development teams, your ability to communicate complex technical concepts clearly is vital. You will be evaluated on how you gather requirements, handle constructive feedback, and align infrastructure initiatives with broader product goals.

The interview process for a DevOps Engineer at Plangrid is comprehensive and designed to thoroughly evaluate both your systems engineering expertise and your software development capabilities. The process typically consists of four to six rounds, moving from initial screening to deep technical evaluations and final leadership conversations.

The loop begins with a standard HR screen to discuss your background, career goals, and mutual alignment on role expectations. This is followed by a technical screening round, which often focuses on core DevOps competencies like scripting, cloud networking, and infrastructure-as-code concepts.

If you pass the initial screens, you will progress to the virtual onsite rounds. This loop typically includes three technical rounds and one hiring manager round. The technical rounds dive deep into systems architecture, CI/CD pipeline design, and hands-on coding. Candidates should be prepared for a rigorous evaluation structure that values practical execution just as much as high-level architectural theory.

The timeline above outlines the typical progression of the interview loop from the initial application to the final decision. Candidates should use this visual guide to pace their preparation, ensuring they allocate ample time to study both systems design and core coding algorithms before entering the intensive onsite stages. While the process usually takes three to four weeks, timelines can adjust based on team availability and level calibration.

Infrastructure as Code & Cloud Platforms

This evaluation area is the core of the DevOps domain. Interviewers want to see that you do not just configure cloud resources manually, but that you treat infrastructure as a software engineering discipline.

Be ready to go over:

• Terraform Best Practices – Writing dry, modular code, managing state safely, and implementing workspace strategies.
• AWS Services – Deep knowledge of VPC networking, IAM policies, EC2, ECS, S3, and RDS.
• State Management – Resolving state locks, handling drift, and importing existing infrastructure into code.
• Advanced concepts (less common) – Multi-cloud orchestration, custom Terraform providers, and advanced IAM federation.

Example scenarios:

• "Design a secure, multi-tier AWS environment using Terraform that isolates database instances from the public internet."
• "How would you safely migrate an active production database to a new AWS account with minimal downtime?"

Coding, Automation & Data Structures

At Plangrid, DevOps is viewed as an engineering discipline. You will be expected to write clean, structured code to automate infrastructure tasks, parse complex data, and build internal tools.

Be ready to go over:

• Scripting Languages – High proficiency in Python, Go, or Bash.
• Data Manipulation – Parsing JSON, YAML, and log files efficiently.
• Algorithms & Data Structures – Basic to intermediate DSA concepts, such as hash maps, queues, and tree traversals.
• Advanced concepts (less common) – Writing custom CLI tools, consuming REST APIs asynchronously, and building custom CI/CD plugins.

Example scenarios:

• "Write a Python script that interacts with the AWS API to identify and terminate unassociated Elastic IPs across all regions."
• "Implement a function that parses a raw application log file and groups error occurrences by their stack trace."

Systems Design & Architecture

This area tests your ability to design large-scale, resilient cloud architectures that support high-concurrency mobile sync applications.

Be ready to go over:

• Scalability – Horizontal vs. vertical scaling, load balancing, and auto-scaling group configurations.
• Resilience – Multi-AZ and multi-region deployments, disaster recovery strategies, and failover mechanisms.
• Caching & Databases – Utilizing Redis, Memcached, and database replication to optimize read/write performance.
• Advanced concepts (less common) – Designing for offline-first data synchronization, global CDN caching strategies, and edge computing.

Example scenarios:

• "Architect a deployment pipeline and infrastructure that can handle a 10x spike in traffic during peak morning sync hours."
• "How would you design a highly available, centralized configuration management service for a fleet of microservices?"