AI/ML Engineer — Generative AI Mission Systems

About this role

<p><strong>AI/ML Engineer — Generative AI Mission Systems</strong></p> <p><strong>Location:</strong> Mainly remote within the United States, with onsite collaboration in Laurel, Maryland, typically one day approximately every six weeks for team-wide sprint planning.<br><strong>Clearance: </strong>Active final DoD Secret clearance required</p> <p>This position supports a pending contract opportunity and is contingent upon contract award, with an anticipated start in November 2026.</p> <p><strong>Build Applied AI for Secure Mission Software</strong></p> <p>Help turn generative-AI concepts into dependable capabilities used within secure mission-planning and decision-support software.</p> <p>At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, prompt-engineering workflows, and inference pipelines into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical application workflows.</p> <p>This role offers the opportunity to deepen your applied-AI experience, influence how emerging capabilities are designed and evaluated, and contribute to software where reliability, security, and mission usefulness matter.</p> <p>This is a primarily remote role within the United States. Work will be performed using customer-provided systems, with virtual collaboration across the engineering team. Any classified work will be completed onsite at the customer location.</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Design, develop, test, and integrate AI-enabled software capabilities.</li> <li>Build and integrate LLM-enabled capabilities into secure application workflows.</li> <li>Develop or integrate retrieval-augmented generation capabilities.</li> <li>Develop and support agentic-AI components and multi-step workflows.</li> <li>Design and refine prompts, system instructions, and supporting AI workflows.</li> <li>Build and maintain inference pipelines.</li> <li>Connect AI capabilities with existing backend services and decision-support processes.</li> <li>Evaluate AI outputs for grounding, reliability, accuracy, relevance, and mission usefulness.</li> <li>Develop tests for AI-enabled functionality and support broader integration testing.</li> <li>Demonstrate working prototypes and incorporate technical and user feedback.</li> <li>Document AI designs, workflows, limitations, evaluation results, and implementation decisions.</li> <li>Participate in code reviews, technical reviews, and security-remediation activities.</li> <li>Collaborate with software engineers, security professionals, DevSecOps teams, and customer stakeholders.</li> </ul> <p><strong>What You Bring</strong></p> <ul> <li>A master’s degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.</li> <li>At least four years of relevant AI/ML experience that includes work with large language models, retrieval-augmented generation, and prompt engineering.</li> <li>Hands-on experience integrating LLM-enabled software and RAG capabilities into applications or workflows.</li> <li>Developing or supporting agentic-AI capabilities and multi-step AI workflows.</li> <li>Designing, building, or supporting inference pipelines.</li> <li>Ability to evaluate AI-enabled capabilities and clearly document findings, design decisions, and results.</li> <li>Testing and documenting AI-enabled software capabilities.</li> <li>Ability to clearly explain your personal technical ownership and contributions.</li> <li>Strong collaboration and technical-communication skills.</li> </ul> <p><strong>Preferred Background</strong></p> <p>Experience with several of the following can strengthen your fit:</p> <ul> <li>Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows.</li> <li>Evaluating grounding, reliability, output quality, hallucinations, or other limitations of AI-enabled systems.</li> <li>Integrating AI services with backend APIs or established software applications.</li> <li>Secure software-development lifecycle and DevSecOps practices.</li> <li>OpenShift, Kubernetes, CI/CD, or containerized application delivery.</li> <li>Secure, restricted, disconnected, on-premises, or classified development environments.</li> <li>Defense, government, aerospace, mission-planning, or other regulated environments.</li> <li>Collaboration with software-engineering, cybersecurity, platform, and customer-facing technical teams.</li> </ul> <p><strong>Why Rackner</strong></p> <p>At Rackner, you will have the opportunity to build technology that supports critical defense and public-sector missions.</p> <p>You will work on more than isolated AI experiments or prompt-engineering tasks. This role combines hands-on LLM integration, retrieval and agentic-AI development, secure software delivery, and close collaboration across AI, software, cybersecurity, DevSecOps, and mission-focused teams.</p> <p>Rackner has delivered more than $30 million in recent federal awards and supports mission-critical work across defense, civilian, and public-sector environments. We are looking for an applied AI engineer who can build on that momentum by turning emerging generative-AI capabilities into secure, dependable software with meaningful mission impact.</p> <p><strong>Benefits &amp; Professional Growth</strong></p> <ul> <li>Competitive compensation</li> <li>Company-supported certifications aligned with current and future program work</li> <li>401(k) with 100% company match up to 6%</li> <li>Medical, dental, vision, life, and disability coverage</li> <li>Paid time off and company holidays</li> <li>Remote-work support and home-office equipment plan</li> <li>Fitness and wellness reimbursement</li>