Quantum Research International, Inc . (Quantum) provides our national defense and federal civilian and industry customers with services and products in the following main areas: 1) Cybersecurity and Information Operations; 2) Space Operations and Control; 3) Aviation Systems; 4) Ground, Air and Missile Defense, and Fires Support Systems; 5) Intelligence Programs Support; 6) Experimentation and Test; 7) Program Management; and (8) Audio/Visual Technology Applications. Quantum's Corporate Office is located in Huntsville, AL, but Quantum actively hires for positions nationwide and internationally. We pride ourselves on providing high quality support to the U.S. Government and our Nation's Warfighters. In addition to our corporate office, we have physical locations in Colorado Springs, CO; Crestview, FL; Orlando, FL; and Tupelo, MS.
Mission
Quantum Research International is seeking an Intermediate DevOps / CI/CD Engineer to support the development, deployment, and operation of a secure Retrieval-Augmented Generation (RAG) application that uses Large Language Models (LLMs) for intelligent inference and response generation.
This government-contract role is focused on building reliable delivery pipelines, automating development and deployment workflows, and maintaining the infrastructure required to operate AI-assisted applications in secure and potentially disconnected environments.
The ideal candidate combines a strong software engineering foundation with practical experience in CI/CD, infrastructure automation, containerized applications, and production operations.
Design, implement, and maintain CI/CD pipelines for application services, RAG components, AI models, and supporting infrastructure.
Integrate automated unit, integration, performance, and security testing into delivery pipelines.
Implement monitoring, logging, alerting, and operational dashboards for AI-assisted applications and their supporting services.
Troubleshoot build, deployment, infrastructure, networking, performance, and availability issues across the delivery lifecycle.
Improve system reliability, scalability, recoverability, and deployment consistency.
Support the secure delivery of locally hosted or self-hosted LLMs, embedding models, vector databases, and RAG services.
Collaborate with software developers, AI/ML engineers, cybersecurity personnel, system administrators, and government stakeholders.
Produce and maintain technical documentation, deployment procedures, operational runbooks, and system configuration records.
Participate in code reviews, release planning, technical demonstrations, and Agile development activities.
Ensure delivery processes and operational environments comply with applicable government security and configuration-management requirements.
Required Skills And Qualifications
Active Top Secret clearance preferred or the ability to obtain and maintain a TS/SCI clearance.
BS degree in equivalent software engineering software programming/development or computer science engineering field
Three or more years of professional experience in software development, DevOps, systems engineering, platform engineering, or a related technical field.
Hands-on experience designing or maintaining CI/CD pipelines using GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins, or a comparable platform.
Experience with source-control workflows, branching strategies, pull or merge requests, release management, and automated quality gates.
Experience deploying and supporting containerized applications using Docker or a comparable container platform.
Proficiency in at least one automation or scripting language, such as Python, PowerShell, Bash, or Go.
Working knowledge of software development in at least one of the following languages: .NET/C#, Go, or Python.
Experience supporting RESTful APIs, microservices, distributed applications, or backend services.
Familiarity with infrastructure-as-code or configuration-management tools such as Terraform, Ansible, Helm, or comparable technologies.
Understanding of Linux-based environments, networking fundamentals, certificates, secrets management, and application configuration.
Experience integrating automated testing, static analysis, dependency scanning, or security scanning into delivery pipelines.
Ability to diagnose build failures, deployment issues, service degradation, and environment inconsistencies.
Understanding of secure software-development and supply-chain practices.
Ability to work effectively with cross-functional engineering, cybersecurity, and program teams.
Desired Skills And Qualifications
Experience operating CI/CD pipelines within secure, classified, air-gapped, or otherwise disconnected environments.
Experience with Kubernetes, OpenShift, Rancher, or similar container-orchestration platforms.
Experience with observability technologies such as Prometheus, Grafana, OpenTelemetry, Elasticsearch, or comparable tools.
Knowledge of software supply-chain security, including software bills of materials, artifact signing, provenance, vulnerability management, and dependency governance.
Experience implementing deployment strategies such as rolling, blue-green, or canary deployments.
Familiarity with government security frameworks and controlled environments, including RMF, NIST guidance, FedRAMP, government cloud platforms, or classified enclaves.
Experience automating system hardening, compliance validation, patching, or configuration auditing.
Familiarity with high-availability design, backup and recovery, disaster recovery, and operational continuity.
One or more relevant professional certifications, such as AWS Certified DevOps Engineer – Professional, Microsoft Certified: DevOps Engineer Expert, Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), HashiCorp Certified: Terraform Associate, Red Hat Certified System Administrator (RHCSA), Red Hat Certified Engineer (RHCE), CompTIA Security+, or a comparable cloud, Linux, container, infrastructure-automation, or security certification.
Experience supporting locally hosted or open-weight AI models and their runtime dependencies.
Familiarity with RAG architectures, embeddings, vector databases, model serving, and AI/ML workflows.
Experience incorporating model, prompt, dataset, or evaluation versioning into automated delivery processes.
Familiarity with MLOps practices, including model packaging, deployment, monitoring, evaluation, and lifecycle management.
Experience supporting GPU-enabled workloads or other specialized AI infrastructure.
Equal Opportunity Employer/Affirmative Action Employer M/F/D/V: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity, or any other characteristic protected by law. *Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
