Description We are hiring an AI/ML Integration Specialist to provide technical direction for bringing approved AI capabilities into an existing federal acquisition enterprise — its toolset, its data, and its accredited infrastructure. Worth being direct about scope: this is an integration role, not a model development role. The hard problems here are schema alignment, API and connector configuration, data readiness, and building the verification and monitoring frameworks that let a security-conscious customer trust an AI-driven output. If you want to train foundation models, this is not that job. If you want to make AI actually work inside a large regulated enterprise, it is. What You'll Get to Do as a AI/ML Integration Specialist: • Evaluate existing and emerging AI tools for integration suitability against real mission requirements. • Analyze current system architectures to determine where AI integration produces value and where it introduces unacceptable risk. • Draft technical roadmaps supporting phased AI adoption, sequenced by dependency and risk rather than by novelty. • Identify and document integration risks, interoperability challenges, and resource requirements. • Define data mapping and schema alignment strategies between source systems and AI tools. • Provide design support for modifying data pipelines to meet AI requirements. • Draft data quality, security, and compliance procedures that make enterprise data fit for AI consumption. • Configure APIs and data connectors for AI services, working alongside platform and security teams. • Document and define technical requirements for interfacing with AI models. • Validate that integrated AI solutions actually match how users work, not just how the architecture diagram says they should. • Design and document continuous verification frameworks that keep AI components secure, usable, and performing within established parameters. • Develop test and evaluation criteria the government can use to validate that integrated AI systems meet mission objectives. • Conduct ongoing technical monitoring and vulnerability assessment, verifying the accuracy, safety, and reliability of AI-driven outputs. Requirements • 5+ years integrating AI and machine learning capabilities into enterprise environments, with at least some of that work inside DoD or federal frameworks. • Master's degree in computer science or data science, or a bachelor's degree with equivalent additional experience. • Active Secret clearance (interim Secret considered with approval). • Hands-on API and data connector configuration, schema mapping, and data pipeline engineering. • Ability to explain AI capability, limitation, and risk to non-technical senior stakeholders without overselling either. Preferred Qualifications: • WS Certified Machine Learning Engineer – Associate, or AWS Certified AI Practitioner. Holders of the retired AWS Certified Machine Learning – Specialty are equally welcome — that credential remains active for three years from the date earned. • Google Cloud Professional Machine Learning Engineer, or comparable current cloud ML credential. • Experience with AI test and evaluation, continuous verification, or security monitoring in an accredited government environment. • Prompt engineering and AI-enabled workflow design experience. • Familiarity with federal AI governance and compliance expectations.