Job Description:Quevera is seeking an
AI/ML Engineer to support mission-critical programs in
Herndon and Springfield, Virginia. This position requires an
active TS/SCI Clearance with Polygraph and supports the design, implementation, and operation of cloud-native infrastructure and AI/ML solutions within secure customer environments.
The successful candidate will design and maintain scalable cloud infrastructure, develop and support AI/ML applications, and build secure deployment pipelines that enable reliable software delivery. Working as part of a collaborative engineering team, you will help architect resilient cloud environments, support production operations, and contribute to the development and deployment of machine learning and generative AI solutions.
Job Responsibilities:- Design, implement, and maintain cloud-native infrastructure and deployment pipelines using Infrastructure as Code (IaC).
- Lead the architecture of scalable, secure, and resilient infrastructure solutions across multiple cloud environments.
- Build and optimize CI/CD pipelines supporting complex microservices architectures.
- Develop and maintain full-stack applications while ensuring operational excellence and system reliability.
- Implement monitoring, logging, and alerting solutions for production environments.
- Design and implement security-first cloud infrastructure solutions.
- Mentor team members on DevOps best practices and cloud-native technologies.
- Participate in on-call production support as needed.
Minimum Requirements:- Active TS/SCI Clearance with Polygraph.
- IC Green Badge (may be obtained as part of the crossover process).
- Bachelor's degree or higher in Science, Technology, Engineering, or Mathematics (STEM).
- Experience in professional software engineering and the full Software Development Life Cycle (SDLC), including coding standards, software architecture, code reviews, source control management, continuous deployments, testing, and operational excellence.
- Three (3) or more years of experience with machine learning, statistical modeling, data analysis tools, and techniques.
- Willingness to work onsite in a SCIF environment at AWS Herndon or the Springfield customer site, up to 100% of the work week.
- Willingness to participate in an on-call production support rotation.
Desired Skills:- Master's degree or higher in Science, Technology, Engineering, or Mathematics (STEM).
- Experience working on multi-team, cross-disciplinary projects.
- Experience applying quantitative analysis to solve business problems and support data-driven decision making.
- Experience defining and creating benchmarks for evaluating Generative AI model performance.
- Experience developing AI/ML solutions using Python, SQL/NoSQL, and APIs.
- Experience working with Large Language Models (LLMs), prompt engineering, and generative AI frameworks.
Why Join Quevera?Award-Winning CultureQuevera was recognized as a
Top Workplace in the Washington, DC/Baltimore region for 2025, marking our
fifth consecutive year receiving this distinction based on employee feedback.
Outstanding BenefitsWe invest in our employees and their families through a highly competitive benefits package, including:
- 100% employer-paid medical coverage (optional plan)
- Competitive options for Medical, Dental and Vision insurance
- Employer-paid short-term and long-term disability coverage
- Employer-paid life insurance
- $5,000 annually for education, training, certifications, and professional development
- Career advancement through our structured iQTouch Program
- Up to 6% 401(k) match
- Additional 4% profit-sharing contribution, at company discretion
At Quevera, we believe exceptional people deserve exceptional opportunities. We're more than just a workplace-we're a team of innovators, problem-solvers, and industry experts committed to delivering mission-critical solutions while fostering professional growth, collaboration, and technical excellence.
Quevera is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age or any other characteristic protected by law. #LI-AA1
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