AI Engineer

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 [email protected].
• 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 [email protected] in advance.
• Application submission: must be submitted directly by the applicant for consideration.