Production AI Engineer Federal & DoD Systems

Job Family: Data Science Consulting

Travel Required: Up to 25%

Clearance Required: Active Secret

Guidehouse is seeking an AI Engineer to support the design, development, validation, and deployment of production‑grade AI‑enabled applications for DoW Federal clients. This role will translate operational workflows, mission needs, and enterprise data assets into secure, scalable, and reliable AI systems.

The AI Engineer will work closely with functional SMEs, architects, data scientists, product managers, and technical delivery teams to build AI‑enabled applications, retrieval workflows, evaluation frameworks, and decision‑support capabilities. This role is focused on delivering working systems, not research prototypes, and must support explainable, auditable, and operationally reliable AI outputs in regulated and mission‑sensitive environments.

• Design, build, and deploy AI‑enabled applications that support real operational workflows and decision‑making for DoW, federal, and enterprise environments.
• Develop application logic that integrates AI models, APIs, data pipelines, user interfaces, and enterprise systems.
• Implement retrieval‑augmented generation, semantic search, embeddings, vector databases, prompt strategies, and agent‑based workflows where appropriate.
• Integrate structured and unstructured enterprise data sources into AI‑enabled applications.
• Build orchestration workflows that connect foundation models, machine learning services, tools, APIs, and secure enterprise environments.
• Develop evaluation frameworks to measure AI output quality, grounding, accuracy, traceability, and failure modes.
• Implement guardrails, validation checks, fallback logic, and human‑in‑the‑loop review points to support reliable AI behavior.
• Support training, tuning, evaluation, and validation of AI or machine learning models using enterprise data while ensuring outputs remain defensible, explainable, and aligned to approved methodologies.
• Develop secure APIs, backend services, dashboards, visualizations, and integration components for AI‑enabled analytic tools and decision‑support platforms.
• Implement monitoring, logging, observability, model performance tracking, and cost controls for AI systems in operation.
• Advise on model transparency, explainability, auditability, data governance, information assurance, and access controls required for secure DoW and federal deployment.
• Collaborate with functional SMEs to translate business needs, mission requirements, workflow requirements, review expectations, and operational constraints into technical requirements.
• Contribute reusable AI components, accelerators, reference architectures, and delivery patterns for future enterprise and federal AI implementations.
• Support demonstrations, pilots, proofs of value, testing, deployment readiness, and user acceptance activities with internal and client stakeholders.

• US Citizenship Required
• An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance.
• Bachelor's degree obtained or equivalent practical experience.
• Experience designing, building, or deploying AI‑enabled applications, analytic tools, decision‑support systems, or machine learning solutions.
• Strong software engineering fundamentals, including APIs, backend services, data pipelines, system integration, and production deployment practices.
• Applied experience with machine learning, generative AI, large language models, retrieval‑augmented generation, embeddings, vector databases, semantic search, or prompt engineering.
• Experience deploying applications or analytic services in cloud or enterprise environments using CI/CD, version control, testing, and secure development practices.

• Experience supporting DoW, federal, national security, or large enterprise technology modernization programs.
• Experience developing or deploying AI‑enabled applications in secure DoW or federal cloud environments.
• Experience with AI‑enabled analytics, predictive modeling, forecasting, scenario analysis, workflow automation, or decision‑support platforms.
• Experience implementing model transparency, explainability, auditability, and traceability controls…