AI/ML Engineer (Active Secret) — Applied AI & Automation
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What you'll do
- Support the responsible integration of artificial intelligence into educational and operational business processes
- Design, develop, test, and deploy AI-driven solutions and process automations
- Conduct AI readiness assessments for proposed use cases
- Perform feasibility, benefit, risk, and implementation analyses using standardized evaluation frameworks
- Evaluate candidate AI use cases based on mission value, data readiness, technical complexity, security, governance, and expected return
- Develop technical supplements to enterprise AI governance frameworks, including:
- AI tool evaluation and adoption criteria
- Model performance monitoring and evaluation protocols
- AI risk and control requirements
- AI incident detection and response procedures
- Human oversight and escalation mechanisms
- Design and implement AI-enabled business process automations using Government-authorized platforms such as Power Automate, Power Apps, Copilot Studio, or comparable workflow and intelligent automation platforms
What they're looking for
- Experience designing, developing, evaluating, or implementing AI/ML solutions
- Experience with responsible AI frameworks, governance, or risk-management practices
- Experience with Power Automate, Copilot Studio, or comparable AI and workflow automation platforms
- Python proficiency
- Experience working with APIs, data sources, and enterprise applications to integrate AI-enabled capabilities
- Experience evaluating, piloting, or deploying AI, machine learning, generative AI, or LLM-based tools in organizational environments
- Understanding of the AI/ML solution lifecycle, including requirements gathering, development, testing, deployment, monitoring, and maintenance
- Experience developing prototypes, proofs of concept, or production AI-enabled applications
- Familiarity with model evaluation, performance measurement, and monitoring approaches
- Ability to assess technical feasibility, business value, implementation complexity, and risk for AI use cases
- Strong analytical, problem-solving, communication, and documentation skills
- Experience working with technical and non-technical stakeholders
Nice to have
- Familiarity with the Department of Defense Responsible AI Strategy and related DoD AI guidance
- Experience developing or implementing AI governance frameworks
- Experience with generative AI and large language models
- Experience building AI agents or agentic workflows
- Experience with retrieval-augmented generation, embeddings, semantic search, or vector databases
- Experience developing intelligent document processing solutions
- Experience with Microsoft Fabric, Azure AI, Azure OpenAI, or related Microsoft cloud AI services
- Experience with Power Platform technologies, including Power Apps and Power Automate
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
AI/ML Engineer — Applied AI & Intelligent Automation
Remote
Active Secret Clearance Required
Build AI That Moves Into Production
Rackner is seeking an AI/ML Engineer to help shape how artificial intelligence is evaluated, built, governed, and deployed across a federal data modernization environment.
This role goes beyond isolated prototypes or model development. You will help determine where AI can create meaningful operational value, whether AI is the right solution, and how promising use cases move from concept into production.
You will have the opportunity to build AI applications, agents, intelligent workflows, and automation while also influencing how emerging AI and LLM technologies are evaluated, governed, monitored, and adopted. Your work may span use-case assessment, solution design, prototyping, testing, deployment, responsible-AI controls, and post-production monitoring.
Working alongside engineering, data, cybersecurity, governance, and mission teams, you will gain visibility across the full AI delivery lifecycle and help shape both the technology and the decisions behind it.
For an engineer who wants to expand beyond a narrow model-development role, this position offers exposure across:
Applied AI engineering → AI/LLM evaluation → intelligent automation → responsible AI → enterprise adoption
You will help turn emerging AI capabilities into practical tools that support real operational needs—not innovation for innovation’s sake.
Then I’d go directly into:
What You’ll Own
- Turn operational challenges into practical AI use cases, technical requirements, and solution designs
- Build and deploy AI applications, agents, intelligent workflows, and process automations
- Take solutions from intake and prototype through testing, production deployment, and monitoring
- Apply Python to AI/ML prototypes, integrations, evaluations, and automation
- Connect AI capabilities with enterprise applications, APIs, workflows, and data platforms
- Create intelligent document workflows for classification, extraction, summarization, routing, and related use cases
- Evaluate AI, generative AI, and LLM platforms for quality, security, reliability, scalability, risk, and organizational fit
- Design pilots, evaluation criteria, test plans, success measures, and adoption recommendations
- Shape responsible-AI controls covering model evaluation, performance monitoring, human oversight, risk, and incident response
- Apply tools such as Power Automate, Power Apps, Copilot Studio, or comparable intelligent-automation platforms
- Develop AI-driven analytics capabilities including predictive modeling, forecasting, and natural-language interaction with enterprise data
- Partner with stakeholders and technical teams to move useful AI capabilities from concept into sustainable operational use
What You'll Bring
- A track record of building, integrating, evaluating, or deploying AI/ML capabilities in real organizational environments
- Strong Python skills
- Hands-on work with generative AI, LLM applications, machine learning, intelligent automation, or related applied-AI technologies
- Ability to integrate solutions with APIs, enterprise systems, workflows, or data sources
- Understanding of the AI delivery lifecycle from requirements and prototyping through testing, deployment, monitoring, and iteration
- Working knowledge of responsible-AI, governance, model evaluation, or AI risk-management practices
- Technical judgment to assess feasibility, value, implementation complexity, and risk
- Ability to translate operational needs into practical technical solutions
- Clear communication across both technical and nontechnical stakeholders
- Active Secret clearance
Valuable Additional Background
You do not need every item below to be successful in the role.
Background in one or more of these areas would be valuable:
- Generative AI and enterprise LLM applications
- AI agents or agentic workflows
- Power Automate, Power Apps, Copilot Studio, or similar automation platforms
- Azure AI, Microsoft Fabric, or related Microsoft technologies
- Intelligent document processing
- Predictive analytics, forecasting, or natural-language analytics
- AI governance, human-in-the-loop controls, model monitoring, or evaluation frameworks
- Organizational AI pilots or technology-selection efforts
- Responsible AI within DoD or other regulated environments
- Federal, defense, or education technology environments
Why Rackner
At Rackner, you will work on technology intended for real mission use—not innovation theater.
This role offers the opportunity to help determine where AI creates value, how solutions should be built, and what responsible production adoption looks like within a complex federal environment.
You will collaborate with teams working across AI/ML, cloud, data, DevSecOps, cybersecurity, and modern software engineering while gaining exposure to both technical delivery and the decisions that shape how emerging technology is adopted.
Rackner is a software consultancy building mission-critical systems for the U.S. government. Our teams support federal agencies and national-security missions through modern cloud, software, data, and AI capabilities.
Benefits & Perks
- Company-supported certifications across AI/ML, cloud, Kubernetes, DevSecOps, security, and related technical areas
- Clear advancement tracks and future leadership opportunities
- 401(k) with 100% match up to 6%
- Medical, dental, vision, life, and disability coverage
- Generous PTO and paid holidays
- Home-office equipment and remote-work support
- Fitness and wellness reimbursement
- Weekly pay
- Team events and professional-development opportunities
Equal Opportunity
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.
Company
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