At M1 Technology, a DevOps Engineer is a vital bridge between software development and systems operations, ensuring that critical applications are deployed rapidly, securely, and reliably. Operating primarily in tech-centric hubs like Chantilly, VA and McLean, VA, the DevOps team is responsible for architecting the infrastructure that powers both commercial solutions and highly secure modern systems. By combining infrastructure automation with backend development capabilities, engineers in this role directly impact the speed of innovation and the resilience of deployed software.

This position is particularly exciting because it often blends core DevOps methodologies with backend development responsibilities. As a DevOps Engineer / Backend Developer, you will not just build pipelines and manage cloud environments; you will also write clean, maintainable backend code, design robust APIs, and optimize database performance. Your work will directly support high-priority engineering initiatives, enabling development teams to release features seamlessly while maintaining a strict security posture.

Ultimately, M1 Technology looks for engineers who treat infrastructure as code and view system reliability as a software problem. You will work on complex, distributed systems where performance, scalability, and security are paramount. If you enjoy solving challenging integration problems, automating away repetitive operational tasks, and contributing to core backend services, this role offers a highly impactful and intellectually stimulating environment.

To succeed in the M1 Technology interview process, you must be prepared to demonstrate both deep operational expertise and strong software engineering fundamentals. The following questions are representative of the technical and behavioral patterns observed in real interview experiences for the DevOps Engineer and DevOps Engineer / Backend Developer roles.

Infrastructure as Code & Cloud Platforms

This category evaluates your ability to design, provision, and manage cloud-native infrastructure securely and programmatically, with a heavy emphasis on AWS and Terraform.

• How do you manage state files in Terraform when working across large, distributed teams?
• Describe a scenario where you had to migrate a legacy on-premises application to AWS. What was your strategy for minimizing downtime?

Preparing for an interview at M1 Technology requires a balanced approach. You cannot simply focus on writing code, nor can you focus solely on system administration. You must demonstrate that you can think like a software developer while operating with the precision of a systems engineer.

Your preparation should focus on demonstrating strength across several core evaluation criteria that the hiring team values highly:

Technical Depth & Systems Thinking – You must understand how operating systems, networks, and cloud services interact under the hood. Interviewers will push you to explain the "why" behind your architectural choices, not just the "how."

Problem-Solving & Troubleshooting – You will be evaluated on your logical progression when diagnosing system failures or debugging code. Be prepared to talk through your debugging process out loud, showing how you isolate variables to find root causes.

Security-First Mindset – Given M1 Technology's presence in key defense and technology corridors, security is never an afterthought. You should naturally weave security practices—such as vulnerability scanning, IAM hardening, and secrets management—into every architectural answer you provide.

Collaborative Leadership – DevOps is as much a culture as it is a set of tools. You need to show that you can build bridges between development and operations teams, advocating for automation and shared responsibility.

The interview process for a DevOps Engineer at M1 Technology is structured to evaluate your technical competency, coding ability, and cultural alignment. The company values a rigorous but transparent hiring process, ensuring that candidates are evaluated fairly on real-world scenarios rather than abstract brainteasers.

The journey typically begins with an initial recruiter screen to align on your background, career goals, and compensation expectations. Following this, you will progress through a technical screening phase, which often includes a practical coding or system design assessment. The final stage is a comprehensive panel interview where you will dive deep into architectural scenarios, backend coding, and behavioral discussions with key team members and hiring managers.

The timeline above details the typical progression from your initial application to the final offer decision. Candidates should use this visual roadmap to pace their preparation, ensuring they allocate sufficient time to practice coding fundamentals before the technical screen, and system architecture design before the final panel. While the exact duration can vary based on team availability and location, the process is designed to be highly communicative and efficient.

To stand out during your interviews, you must demonstrate mastery in several distinct technical domains. The engineering team at M1 Technology will evaluate your skills through practical discussions and hands-on exercises in these key areas.

Infrastructure as Code & Cloud Platforms

This area evaluates your ability to manage infrastructure programmatically, ensuring environments are reproducible, scalable, and secure. You must show a deep understanding of cloud resource provisioning and architecture.

Be ready to go over:

• Terraform Module Design – How to build reusable, dry, and highly configurable Terraform modules.
• AWS Networking – Designing secure VPC architectures, including public/private subnets, NAT gateways, security groups, and NACLs.
• State Management – Best practices for state locking, remote backends, and handling state drift.

Advanced concepts (less common):

• Multi-region failover configurations and active-active deployments.
• Writing custom Terraform providers or integrating open-source policy-as-code tools like OPA (Open Policy Agent).

Example questions or scenarios:

• "Walk me through how you would structure Terraform code to manage dev, staging, and production environments while minimizing code duplication."
• "How would you design a secure, multi-tier AWS VPC architecture for a backend application that requires database access but must not be exposed to the public internet?"

CI/CD & Container Orchestration

This evaluation area focuses on your ability to build highly efficient pipelines and manage containerized workloads at scale, ensuring rapid feedback loops for developers.

Be ready to go over:

• Pipeline Optimization – Strategies for reducing build and deployment times, such as caching dependencies and parallel execution.
• Kubernetes Core Concepts – Understanding Pods, Deployments, Services, Ingress, and ConfigMaps/Secrets.
• Deployment Strategies – Implementing blue-green, canary, and rolling update deployments.

Advanced concepts (less common):

• GitOps workflows using tools like ArgoCD or Flux.
• Writing custom Kubernetes operators or managing complex Helm charts.

Example questions or scenarios:

• "How would you design a canary deployment strategy for a microservice deployed on a Kubernetes cluster? How do you determine if a rollback is necessary?"
• "Explain how you would integrate automated security scanning (SAST/DAST) into a Jenkins or GitLab CI pipeline without significantly slowing down the build process."

Backend Development & Scripting

As a DevOps Engineer / Backend Developer, you must possess strong software engineering capabilities. This area tests your ability to write clean, efficient code and design robust backend systems.

Be ready to go over:

• API Design – Developing secure, RESTful, or gRPC-based endpoints.
• Scripting & Automation – Writing robust scripts in Python, Go, or Bash to automate complex operational workflows.
• Database Integration – Interfacing backend applications with relational (PostgreSQL) and non-relational databases.

Advanced concepts (less common):

• Concurrency patterns in Go (goroutines/channels) or asynchronous programming in Python.
• Optimizing database queries, indexing strategies, and analyzing execution plans.

Example questions or scenarios:

• "Write a backend service endpoint that processes incoming webhooks, validates the payload, and writes the data to a database while handling potential connection failures gracefully."
• "Describe how you would design an automated cleanup script that identifies and deletes unassociated AWS EBS volumes, ensuring you don't accidentally delete critical data."