Guidehouse

Data Science Consulting

AI/DataEngineer

$106–176k United States FULL TIME Remote Friendly
The Brief

“AI / Data Engineer at Guidehouse. Skills: AI-enabled applications, Machine Learning, Generative AI, Data Pipelines. Design, build, deploy AI-enabled applications. Develop application logic”

What You'll Achieve.

Deliver working systems; Support explainable, auditable, reliable AI outputs; Support real operational workflows; Support decision-making; Ensure outputs remain defensible, explainable, aligned; Support secure DoW and federal deployment; Move AI solutions from concept to production-ready services

Industry & Context.

Data Science Consulting
Problems you'll solve

Structured problem-solving skills

Eligibility Requirements

Up to 25% Travel, Active Secret Clearance, US Citizenship Required

What They're Looking For.

Must Have

US Citizenship Required, 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, 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

Nice to Have

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, LangChain, LlamaIndex, 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, 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

What You'll Do.

deploy AI-enabled applications

Develop application logic

Implement retrieval-augmented generation

Integrate enterprise data sources

Build orchestration workflows

Develop evaluation frameworks

Advise on model transparency

Collaborate with functional SMEs

Contribute reusable AI components

Support demonstrations

How You'll Work.

Team & Collaboration

Work closely with functional SMEs; Collaborate with architects; Work with data scientists; Partner with product managers; Engage with technical delivery teams; Collaborate with functional SMEs; Communicate technical concepts to stakeholders

Communication Scope

Communicate technical concepts clearly

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