AI/ML Engineer at Rackner
Worldwide
<p><strong>AI/ML Specialist</strong></p> <p class="isSelectedEnd"><strong>Location:</strong> Remote<br><strong>Clearance Level:</strong> Active Secret</p> <p><strong>Overview</strong></p> <p class="isSelectedEnd">Rackner is seeking an AI/ML Specialist to support the responsible design, development, evaluation, and deployment of artificial intelligence and automation capabilities across educational and operational environments.</p> <p class="isSelectedEnd">The AI/ML Specialist will help identify high-value AI use cases, assess technical and organizational readiness, develop and deploy AI-enabled solutions, and support governance, monitoring, and adoption activities. This role will work across stakeholders, technical teams, data teams, and program leadership to integrate AI capabilities into existing business processes while ensuring solutions align with responsible AI principles, Government policy, and organizational strategy.</p> <p class="isSelectedEnd">The AI/ML Specialist will also support the evaluation of emerging AI and large language model platforms, develop intelligent automation solutions, and contribute to AI governance, procurement readiness, and enterprise adoption.</p> <p><strong>Responsibilities</strong></p> <ul data-spread="false"> <li>Support the responsible integration of artificial intelligence into educational and operational business processes</li> <li>Design, develop, test, and deploy AI-driven solutions and process automations</li> <li>Conduct AI readiness assessments for proposed use cases</li> <li>Perform feasibility, benefit, risk, and implementation analyses using standardized evaluation frameworks</li> <li>Evaluate candidate AI use cases based on mission value, data readiness, technical complexity, security, governance, and expected return</li> <li>Develop technical supplements to enterprise AI governance frameworks, including: <ul data-spread="false"> <li>AI tool evaluation and adoption criteria</li> <li>Model performance monitoring and evaluation protocols</li> <li>AI risk and control requirements</li> <li>AI incident detection and response procedures</li> <li>Human oversight and escalation mechanisms</li> </ul> </li> <li>Design and implement AI-enabled business process automations using Government-authorized platforms such as: <ul data-spread="false"> <li>Power Automate</li> <li>Power Apps</li> <li>Copilot Studio</li> <li>Comparable workflow and intelligent automation platforms</li> </ul> </li> <li>Develop AI-enabled solutions through established solution delivery processes, including: <ul data-spread="false"> <li>Intake and requirements assessment</li> <li>Solution design</li> <li>Prototype development</li> <li>Testing and validation</li> <li>Security and governance review</li> <li>Production deployment</li> <li>Post-deployment monitoring</li> </ul> </li> <li>Build and maintain AI agents and agent-enabled workflows</li> <li>Develop intelligent document processing capabilities for classification, extraction, summarization, routing, and related use cases</li> <li>Integrate AI capabilities with enterprise applications, data platforms, APIs, and workflow systems</li> <li>Develop and maintain automated workflows incorporating AI or machine learning components</li> <li>Support AI tool evaluation, pilot program development, and proof-of-concept initiatives</li> <li>Develop evaluation criteria, test plans, success metrics, and recommendations for AI pilots</li> <li>Evaluate emerging AI, machine learning, generative AI, and large language model platforms for organizational applicability</li> <li>Assess Department of Defense-developed, Government-provided, and commercially acquired AI/LLM platforms</li> <li>Support procurement readiness activities for AI tools, including requirements definition, technical evaluation, risk identification, and adoption criteria</li> <li>Develop AI-enabled analytics capabilities including: <ul data-spread="false"> <li>Predictive modeling</li> <li>Forecasting</li> <li>Natural-language query</li> <li>Classification and anomaly detection</li> <li>Decision-support capabilities</li> </ul> </li> <li>Support development of semantic models and AI-ready data products within enterprise Lakehouse environments</li> <li>Develop Python-based AI/ML prototypes, integrations, evaluations, and automation components</li> <li>Support model and solution testing for accuracy, performance, reliability, bias, robustness, and operational suitability</li> <li>Establish and maintain model performance metrics and monitoring processes</li> <li>Support identification, triage, documentation, and response for AI-related incidents or unexpected model behaviors</li> <li>Collaborate with data engineers, analysts, governance teams, cybersecurity teams, and application developers to operationalize AI capabilities</li> <li>Translate stakeholder needs into AI use cases, technical requirements, solution designs, and acceptance criteria</li> <li>Support stakeholder engagement, demonstrations, workshops, training, and adoption activities</li> <li>Develop technical documentation, implementation guides, evaluation reports, and user-facing materials</li> <li>Support change management and adoption efforts for AI-enabled processes</li> <li>Ensure AI solutions align with applicable organizational AI strategies, AI guidelines, security requirements, and responsible AI principles</li> </ul> <p><strong>Qualifications</strong></p> <ul data-spread="false"> <li>Experience designing, developing, evaluating, or implementing AI/ML solutions</li> <li>Experience with responsible AI frameworks, governance, or risk-management practices</li> <li>Experience with Power Automate, Copilot Studio, or comparable AI and workflow automation platforms</li> <li>Python proficiency</li> <li>Experience working with APIs, data sources, and enterprise applications to integrate AI-enabled capabilities</li> <li>Experience evaluating, piloting, or deploying AI, machine learning, generative AI, or LLM-based tools in organizational environments</li> <li>Understanding of the AI/ML solution lifecycle, including requirements gathering, development, testing, deployment, monitoring, and maintenance</li> <li>Experience developing prototypes, proofs of concept, or production AI-enabled applications</li> <li>Familiarity with model evaluation, performance measurement, and monitoring approaches</li> <li>Ability to assess technical feasibility, business value, implementation complexity, and risk for AI use cases</li> <li>Strong analytical, problem-solving, communication, and documentation skills</li> <li>Experience working with technical and non-technical stakeholders</li> <li>Ability to translate operational needs into practical AI-enabled solutions</li> <li>Active Secret clearance</li> </ul> <p><strong>Preferred Qualifications</strong></p> <ul data-spread="false"> <li>Familiarity with the Department of Defense Responsible AI Strategy and related DoD AI guidance</li> <li>Experience developing or implementing AI governance frameworks</li> <li>Experience with generative AI and large language models</li> <li>Experience building AI agents or agentic workflows</li> <li>Experience with retrieval-augmented generation, embeddings, semantic search, or vector databases</li> <li>Experience developing intelligent document processing solutions</li> <li>Experience with Microsoft Fabric, Azure AI, Azure OpenAI, or related Microsoft cloud AI services</li> <li>Experience with Power Platform technologies, including Power Apps and Power Automate</li> <li>Experience developing predictive analytics, forecasting, or natural-language analytics capabilities</li> <li>Experience with model evaluation frameworks, guardrails, human-in-the-loop controls, or AI observability</li> <li>Experience evaluating AI tools for security, privacy, reliability, bias, and organizational fit</li> <li>Experience supporting AI procurement, technology selection, or pilot programs</li> <li>Familiarity with AI capabilities within enterprise Lakehouse or semantic-model architectures</li> <li>Experience within Department of Defense, federal, or education environments</li> </ul> <p><strong>About Rackner</strong><br>Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. Our teams work across cloud platforms, DevSecOps, AI/ML, distributed systems, and modern software engineering initiatives supporting federal agencies and national security missions. Rackner engineers and technical teams collaborate closely with leadership, program teams, and mission stakeholders to design, demonstrate, and improve software systems that address complex operational challenges.</p> <p> </p> <p><strong>Benefits & Perks</strong><br>At Rackner, we believe that when our people grow, our company grows with them, and we are committed to supporting their growth, development and success. We are proud to offer a creative and forward-thinking environment that includes:<br>• Company-supported certifications aligned to current and future program work, <br>including cloud, Kubernetes, DevSecOps, security, AI/ML, project management, and <br>related technical areas<br>• Clear advancement tracks and future leadership opportunities<br>• 401(k) with 100% match up to 6%<br>• Comprehensive medical, dental, vision, life, and disability coverage<br>• Generous PTO and paid holidays<br>• Home-office equipment plan and remote work support<br>• Fitness and wellness reimbursement<br>• Weekly pay schedule and modern perks, including team events</p> <p> </p> <p><strong>Equal Opportunity</strong><br>Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.</p>
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