AI​/Data Engineer

Job Family and Travel

Data Science Consulting.

Travel Required:

Up to 25%.

Clearance Required:

Active Secret.

• 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 and 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 for AI-generated recommendations or analytic outputs.
• Experience designing dashboards, visualizations, or user-facing applications for complex analytical workflows.
• Understanding of information assurance, cybersecurity, access controls, and secure deployment considerations for DoW, federal, or enterprise environments.
• Experience with Python, FastAPI, Lang Chain, Llama Index, Azure AI, AWS, Databricks, Snowflake, vector databases, containerized deployments, or related AI engineering tools.
• Experience contributing reusable components, accelerators, or reference architectures for enterprise AI delivery.
• Prior experience supporting demonstrations, pilots, proofs of value, testing, deployment readiness, or user acceptance activities with DoW or federal client stakeholders.
• Ability to move AI solutions from concept or prototype into production-ready services.
• Understanding of evaluation approaches for AI systems, including accuracy testing, grounding, validation, failure analysis, and human review workflows.
• Familiarity with data quality challenges, structured and unstructured data integration, and enterprise data governance.
• Ability to communicate technical concepts clearly to functional SMEs, product owners, architects, and non-technical stakeholders.
• Strong structured problem-solving skills and ability to design systems that are reliable, explainable, secure, and operationally usable.
• Comfort operating in regulated, audit-sensitive, federal, or DoW environments.

Full-time support, approximately 1.0 FTE during solution design, data integration, AI…