AI Engineer (AI)

Location: Remote within the United States; occasional onsite meetings at the client site in Washington, DC. U.S. citizenship, U.S. residency, U.S. work authorization, and three full years of U.S. residence within the last five years are required. All work must be performed in the U.S.

Salary: $108,476.00–$184,409.00 per year.

Company

hirify.global is an advisory and technology services provider delivering cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation solutions for federal clients.

What you will do

• Develop NLP, text analytics, generative AI, prompt orchestration, guardrails, content filtering, and human-in-the-loop workflows.
• Build reusable AI/ML solutions, model deployment frameworks, agentic workflows, and MLOps pipelines.
• Translate unstructured-data use cases into repeatable patterns covering privacy, provenance, evaluation, monitoring, and operational integration.
• Collaborate with Trustworthy AI, security, data governance, engineering, product, quality, and customer-facing stakeholders.
• Document technical decisions, risks, work products, and delivery evidence to support traceability and continuous improvement.

Requirements

• U.S. citizenship and U.S. work authorization are required; all work must be performed in the U.S.
• Must reside in the U.S. and 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; a master’s degree may substitute for two years of relevant experience.
• At least six years of experience designing, developing, and deploying AI/ML solutions in enterprise cloud environments.
• Strong programming experience with Python, SQL, and modern AI/ML libraries and frameworks.
• Experience with Azure, Databricks, Azure Machine Learning, MLflow, cloud-scale data platforms, and MLOps practices.

Nice to have

• Experience with LLMs, RAG, semantic search, vector databases, prompt engineering, Azure OpenAI, LangChain, or Semantic Kernel.
• Experience with AI safety controls, model evaluation, monitoring, versioning, automated retraining, and responsible AI practices.
• Experience with data governance, metadata management, data lineage, privacy controls, and role-based access models.
• Experience supporting federal government, healthcare, or other regulated environments.

Culture & Benefits

• Full-time employment with a nationwide remote work arrangement.
• Occasional onsite client meetings in Washington, DC.
• Work across engineering, architecture, data science, product, governance, security, and business functions.
• Work location monitoring is used, foreign locations and foreign IP addresses are blocked, and personal VPN connections are prohibited.