AI Engineer

Description

Please note: This role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award.

The Work

At ICF our Digital Modernization Division is an information technology and management consulting organization that delivers integrated, strategic solutions to federal clients. We bring expertise in cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation to support mission-critical government programs.

Join a team accelerating the modernization of a large federal agency's enterprise data and analytics ecosystem. This cloud-based platform provides data storage, analytics, governance, and AI/ML capabilities that enable thousands of users to transform data into actionable insights. As demand continues to grow, the team is focused on migrating legacy workloads, streamlining onboarding and support, expanding platform capabilities, and helping organizations across the enterprise adopt modern data and AI solutions at scale.

The AI Engineer develops and operationalizes AI, machine learning, NLP, predictive analytics, and generative AI capabilities that accelerate data-driven decision making across the enterprise. This role builds reusable AI/ML solutions, model deployment frameworks, prompt orchestration patterns, agentic workflows, and MLOps pipelines leveraging Databricks ML, Azure Machine Learning, MLflow, Python, and cloud-scale data platforms. Working across engineering, governance, security, and business teams, the AI Engineer enables the adoption of AI at scale through model monitoring, performance evaluation, human-in-the-loop workflows, cost optimization, and responsible AI practices that ensure solutions are trusted, governed, and production-ready.

Job Location: Remote, however, strong preference for candidates who live in the Washington DC Metro Area. There will be occasional onsite meetings on the client site in Washington, DC.

*

If you accept this position, you should note that ICF does monitor employee work locations, blocks access from foreign locations/foreign IP addresses, and prohibits personal VPN connections.

What You Will Do

• Develops NLP, text analytics, prompt orchestration, guardrails, content-filtering approaches, and human-in-the-loop workflows using VA-approved AI/ML tools and data environments.
• Translates unstructured-data use cases into repeatable technical patterns that address privacy, provenance, evaluation, monitoring, and operational integration.
• Works 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 to support role delivery.
• Collaborate with relevant product, engineering, security, governance, quality, and customer-facing stakeholders as required by the role.
• Document work products, decisions, risks, and delivery evidence to support traceability and continuous improvement.

Basic Qualifications

• U.S. Citizenship is required due to federal contract requirements.
• Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S.
• Candidate 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; Master's degree may substitute for two (2) years of relevant experience.
• 6+ years of designing, developing, and deploying AI/ML solutions in enterprise cloud environments.

Preferred Qualifications

• Hands-on experience with large language models (LLMs), generative AI, natural language processing (NLP), retrieval-augmented generation (RAG), semantic search, vector databases, and prompt engineering techniques.
• 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 using Python, SQL, and 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, document intelligence, text analytics, classification, summarization, recommendation, and generative AI use cases.
• 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 with CI/CD practices utilizing GitHub
• Experience working in Agile, cross-functional teams consisting of engineers, architects, data scientists, product owners, governance stakeholders, and business users.
• Experience supporting Federal government, healthcare, or other highly regulated environments is preferred.

Professional Skills

• Highly effective analytical, problem-solving, and decision-making capabilities.
• Excellent written and verbal communication skills, with the ability to work effectively across technical and non-technical audiences.

*