AI/ML Engineer (Active Secret) — Applied AI & Automation

Remote
Active Secret Clearance Required

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:

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:

• 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

• 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

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

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.

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.