AI/ML Engineer

Role overview

Design, evaluate, and deploy responsible AI and machine-learning capabilities across educational and operational environments. The role combines hands-on Python development and workflow automation with AI readiness analysis, governance, stakeholder engagement, and production monitoring. It is remote and requires an active Secret clearance.

Responsibilities

- Identify and assess AI use cases by mission value, data readiness, feasibility, risk, security, governance, and expected return. - Design, prototype, test, deploy, and monitor AI-enabled applications, agents, automations, and intelligent document-processing workflows. - Build integrations with enterprise applications, APIs, data platforms, workflow systems, and semantic or Lakehouse-based data products. - Develop governance materials covering tool evaluation, model performance, risk controls, incident response, human oversight, and escalation procedures. - Evaluate generative AI, machine-learning, and large-language-model platforms through pilots, proof-of-concepts, test plans, success metrics, and technical recommendations. - Collaborate with engineers, analysts, cybersecurity teams, governance stakeholders, and business users; produce documentation, demonstrations, training, and adoption materials.

Requirements

- Experience designing, developing, evaluating, or implementing AI/ML solutions and prototypes or production applications. - Proficiency in Python, with experience integrating APIs, data sources, and enterprise applications. - Experience with Power Automate, Copilot Studio, or comparable AI and workflow-automation platforms. - Understanding of the full AI/ML lifecycle, including requirements, development, testing, deployment, monitoring, maintenance, and performance evaluation. - Ability to assess technical feasibility, business value, implementation complexity, operational suitability, and risk. - Strong analytical, problem-solving, communication, documentation, and cross-functional collaboration skills. - Experience with responsible AI, governance, risk management, or related control frameworks. - Active Secret clearance and familiarity with federal or defense AI guidance.

Nice to have

Experience with generative AI, LLMs, AI agents, retrieval-augmented generation, embeddings, semantic search, vector databases, intelligent document processing, predictive analytics, forecasting, model observability, Microsoft cloud AI services, enterprise Lakehouse architectures, or federal, defense, or education environments.