AI Engineer

ICF

. Develop NLP, text analytics, prompt orchestration, guardrails, content-filtering approaches, and human-in-the-loop workflows using VA-approved AI/ML tools and data environments .

Posted 10/8/2026full-timeUnited StatesMid-LevelSenior💰 $108,476 - $184,409 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and operationalizing AI/ML solutions, particularly in NLP and generative AI, while ensuring compliance with data governance and safety standards. Proficient in collaborating across teams to enhance AI capabilities and optimize performance in regulated environments.

Highest-signal resume keywords

AI/ML Solution DevelopmentNatural Language Processing (NLP)Azure AI ServicesMLOps Pipeline DevelopmentGenerative AI Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingSQLMachine LearningPredictive AnalyticsText AnalyticsPrompt EngineeringModel DeploymentData IntegrationContent FilteringAI Safety Controls

Soft Skills

Analytical Problem-SolvingDecision-MakingWritten CommunicationVerbal CommunicationOrganizational Skills

Tools & Technologies

Azure OpenAIDatabricks AI/MLMLflowLangChainSemantic KernelDelta LakeAzure Machine LearningGitHubCI/CD PracticesAgile Methodologies

Industry Keywords

Data GovernancePrivacy ControlsHuman-in-the-Loop WorkflowsTrustworthy AIRegulated Environments

Tech Stack

Tools & technologies

AzureCloudPythonSQL

About the role

Key responsibilities & impact

Develop NLP, text analytics, prompt orchestration, guardrails, content-filtering approaches, and human-in-the-loop workflows using VA-approved AI/ML tools and data environments
Translate unstructured-data use cases into repeatable technical patterns addressing privacy, provenance, evaluation, monitoring, and operational integration
Work with Trustworthy AI, Security, Data Governance, and Customer Experience personnel to ensure generative-AI capabilities are safe, useful, and governed
Apply NLP, LLM/GenAI patterns, prompt orchestration, retrieval/evaluation patterns, guardrails, content filters, human-in-the-loop workflows, and Azure AI
Collaborate with product, engineering, security, governance, quality, and customer-facing stakeholders
Document work products, decisions, risks, and delivery evidence to support traceability and continuous improvement
Build reusable AI/ML solutions, model deployment frameworks, prompt orchestration patterns, agentic workflows, and MLOps pipelines
Operationalize AI, machine learning, NLP, predictive analytics, and generative AI capabilities
Support model monitoring, performance evaluation, human-in-the-loop workflows, cost optimization, and responsible AI practices
Accelerate modernization of a federal agency's enterprise data and analytics ecosystem

Requirements

What you’ll need

U.S. Citizenship is required due to federal contract requirements
Candidate must reside in the U.S. and be authorized to work in the U.S.
All work must be performed in the U.S.
Candidate must have lived in the U.S. for three full years out of the last five years
Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field
Master's degree may substitute for two years of relevant experience
6+ years of designing, developing, and deploying AI/ML solutions in enterprise cloud environments
Preferred: hands-on experience with LLMs, generative AI, NLP, RAG, semantic search, vector databases, and prompt engineering
Preferred: experience with Azure AI Services, Azure OpenAI, Databricks AI/ML, MLflow, LangChain, Semantic Kernel, or similar frameworks
Preferred: experience developing prompt orchestration, evaluation frameworks, model testing strategies, and AI application monitoring solutions
Preferred: experience implementing AI safety controls, content filtering, guardrails, human-in-the-loop review processes, and Trustworthy AI practices
Preferred: experience developing and maintaining MLOps pipelines, model deployment frameworks, model versioning, performance monitoring, and automated retraining
Preferred: strong programming experience using Python, SQL, and modern AI/ML libraries and frameworks
Preferred: experience with Databricks, Delta Lake, Azure Machine Learning, and enterprise-scale data platforms
Preferred: experience integrating AI solutions with cloud-native data pipelines, analytics platforms, APIs, and operational business applications
Preferred: experience supporting predictive analytics, document intelligence, text analytics, classification, summarization, recommendation, and generative AI use cases
Preferred: familiarity with enterprise data governance, metadata management, data lineage, privacy controls, and role-based access models in regulated environments
Preferred: experience optimizing AI/ML workloads for performance, scalability, reliability, and cloud cost management
Preferred: experience with CI/CD practices utilizing GitHub
Preferred: experience working in Agile, cross-functional teams
Preferred: experience supporting Federal government, healthcare, or other highly regulated environments
Highly effective analytical, problem-solving, and decision-making capabilities
Excellent written and verbal communication skills
Strong organization, attention to detail, prioritization, and ability to manage multiple responsibilities
Collaborative approach with commitment to quality, accountability, and continuous improvement

Benefits

Comp & perks

Remote work arrangement
Occasional onsite meetings on the client site in Washington, DC
Equal opportunity employer
Reasonable accommodations for disabilities, disabled veterans, and sincerely held religious beliefs
Confidential accommodation support
Benefits information provided through Transparency in Coverage Act materials