Full-Time
Automated Test Engineer
Booker DiMaio
1-10 employees
IT modernization and software engineering
No salary listed
No H1B Sponsorship
Annapolis Junction, MD, USA
Hybrid
On-site in Annapolis Junction with 1–2 remote days per week depending on tasking.
US Top Secret Clearance Required
 QA & Testing (1) |
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- An active Top Secret/Sensitive Compartmented Information clearance with a Full Scope Polygraph is required.
- Proven experience designing, writing, and maintaining automated tests using Cypress.
- Proficiency in JavaScript or TypeScript for test script development.
- Experience testing modern web applications, Representational State Transfer (RESTful) microservices, and application programming interfaces (APIs).
- Strong understanding of software quality assurance methodologies, tools, and processes.
- Practical experience with Agile software development methodologies and collaboration tools such as Jira and Confluence.
- Experience with version control systems using Git.
- Independently design, develop, and maintain high-quality, scalable automated user interface and application programming interface test scripts utilizing Cypress.
- Execute automated test suites, analyze results, troubleshoot failures, and comprehensively document defects and testing metrics.
- Partner with DevOps and software engineers to integrate automated testing into the continuous integration and continuous delivery pipeline, such as GitLab CI/CD.
- Participate in Agile ceremonies, including sprint planning and demonstrations, and work with the team to understand functional requirements and ensure comprehensive test coverage for new features and bug fixes.
- Experience configuring and integrating automated tests within continuous integration and continuous delivery pipelines, such as GitLab CI/CD.
- Familiarity with cloud-based architecture and deployment using Amazon Web Services.
- Basic understanding of containerization using Docker to test applications in consistent environments.
- Familiarity with domain knowledge surrounding government agency reporting and dissemination policies.
Booker DiMaio helps government and national security clients modernize their technology with engineering and software transformation services. Its offerings span end-to-end tech services and a reseller-enabled portfolio from AWS, Microsoft Azure, FedRAMP Cloud Solutions, and SecuLore, combining cloud, analytics, DevSecOps, cybersecurity, and IT modernization delivered by cross-functional teams focused on mission needs and regulatory compliance. The company differentiates itself by assigning dedicated, project-specific teams with 90+ years of combined experience, a broad end-to-end solutions set, and a proven emphasis on user experience and compliance. Its goal is to help defense, intelligence, and civilian customers transform operations through practical, compliant, and effective software and infrastructure solutions.
Company Size
1-10
Company Stage
N/A
Total Funding
N/A
Headquarters
Sykesville, Maryland
Founded
2010
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Simplify's Take
What believers are saying
- A December 31, 2025 Army purchase order added CYBER TRAINING PLATFORM revenue.
- LinkedIn shows 1,143 followers, giving Booker DiMaio a visible recruiting and sales channel.
- ServiceNow's 2026 partner ecosystem keeps Booker DiMaio aligned with active enterprise AI demand.
What critics are saying
- Booker DiMaio remains tiny, with PitchBook showing 11 employees and fragile execution capacity.
- Federal obligations totaled $3.98 million across four awards, limiting revenue diversification.
- A contract lapse after August 2026 would hit cash flow and hiring immediately.
What makes Booker DiMaio unique
- Sean Booker runs a 11-50 person Maryland engineering firm founded in 2010.
- Booker DiMaio holds a ServiceNow partnership and markets enterprise AI workflow implementations.
- The firm won SeaPort NxG and GSA vehicles, supporting federal access.
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Benefits
Remote Work Options
Company News
Booker DiMaio has partnered with ServiceNow, currently the most effective resource for artificial intelligence (AI) and machine learning.