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AI Engineer

ICF Reston, VA 🇺🇸 Remote

Reston, VA

Today

$108k - $184k/yr Full time Agentic Ai Artificial Intelligence Artificial Intelligence Engineer

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Job Description

ICF is hiring an AI Engineer to develop and operationalize AI/ML, NLP, predictive analytics, and generative AI for a cloud-based federal enterprise data and analytics platform.

Responsibilities

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.
Convert unstructured-data use cases into repeatable technical patterns covering privacy, provenance, evaluation, monitoring, and operational integration.
Partner with Trustworthy AI, Security, Data Governance, and Customer Experience teams to ensure generative-AI capabilities are safe, useful, and governed.
Apply NLP, LLM/GenAI patterns, retrieval and evaluation approaches, guardrails, content filters, human-in-the-loop workflows, and Azure AI to support role delivery.
Collaborate with product, engineering, security, governance, quality, and customer-facing stakeholders as required by the role.
Document deliverables, decisions, risks, and delivery evidence to support traceability and continuous improvement.

Requirements

U.S. Citizenship required due to federal contract requirements.
Must reside in the U.S., be authorized to work in the U.S., and perform all work in the U.S.
Must have lived in the U.S. for three (3) full years out of the last five (5) years.
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field; a Master’s degree may substitute for two (2) years of relevant experience.
6+ years designing, developing, and deploying AI/ML solutions in enterprise cloud environments.

Preferred Qualifications

Hands-on experience with large language models (LLMs), generative AI, NLP, retrieval-augmented generation (RAG), semantic search, vector databases, and prompt engineering.
Experience building AI applications and agentic workflows using Azure AI Services, Azure OpenAI, Databricks AI/ML, MLflow, LangChain, Semantic Kernel, or similar frameworks.
Experience developing prompt orchestration, evaluation frameworks, model testing strategies, and AI application monitoring solutions.
Experience implementing AI safety controls, content filtering, guardrails, human-in-the-loop review processes, and Trustworthy AI practices.
Experience developing and maintaining MLOps pipelines, model deployment frameworks, model versioning, performance monitoring, and automated retraining processes.
Strong programming experience with Python and SQL, plus modern AI/ML libraries and frameworks.
Experience with Databricks, Delta Lake, Azure Machine Learning, and enterprise-scale data platforms.
Experience integrating AI solutions with cloud-native data pipelines, analytics platforms, APIs, and operational business applications.
Experience supporting predictive analytics and generative AI use cases such as document intelligence, text analytics, classification, summarization, and recommendation.
Familiarity with enterprise data governance, metadata management, data lineage, privacy controls, and role-based access models in regulated environments.
Experience optimizing AI/ML workloads for performance, scalability, reliability, and cloud cost management.
Experience using CI/CD practices with GitHub.
Experience working in Agile, cross-functional teams including engineers, architects, data scientists, product owners, governance stakeholders, and business users.
Experience supporting Federal government, healthcare, or other highly regulated environments is preferred.

Technologies

Databricks ML, Azure Machine Learning, MLflow
Python, SQL
NLP, AI/ML, generative AI, LLM, GenAI
Prompt orchestration, agentic workflows, MLOps pipelines
VA-approved AI/ML tools, Azure AI, Azure OpenAI
LangChain, Semantic Kernel
Retrieval-augmented generation (RAG), retrieval/evaluation patterns, semantic search
Vector databases
Databricks AI/ML, Delta Lake, cloud-scale data platforms
Text analytics
Guardrails, content filtering, human-in-the-loop workflows, model monitoring, performance evaluation, cost optimization
GitHub, CI/CD

Location

Reston, VA (remote)
Remote with strong preference for candidates who live in the Washington DC Metro Area.
Occasional onsite meetings on the client site in Washington, DC.

Compensation

Pay range: USD 108,476 - 184,409 per year
Nationwide Remote Office: US99

Additional Information

Reasonable accommodations are available, including for disabled veterans and individuals with disabilities.
To request an accommodation, email Candidateaccommodation@icf.com.
Information provided for accommodations is kept confidential and used only as required to provide the needed reasonable accommodations.
Candidate AI usage policy: use of AI tools to generate or assist with interview responses (in-person or virtual) is not permitted.
Candidates needing accommodation that involves AI should contact Candidateaccommodation@icf.com in advance.
Application submission: must be submitted directly by the applicant for consideration.

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