AI/ML SME

Globenet Consulting Corp•BELLEVUE, WA

2d•$140,000 - $165,000•Onsite

About The Position

We are seeking an experienced AI/ML Engineer to design, develop, and deploy scalable AI-powered applications and machine learning solutions. The role requires strong Python development skills and hands-on experience with large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and enterprise AI integration. The position is onsite in Fort Belvoir, Virginia, and is primarily office-based, with collaboration across technical and engineering teams.

Requirements

Active Secret Security Clearance (minimum); mandatory.
CompTIA Security+ certification; mandatory.
Minimum 3 years of experience in software engineering, application development, or AI/ML engineering.
Strong hands-on experience developing Python applications, APIs, and backend services.
Practical experience building Generative AI, LLM, or machine learning applications.
Experience with LangChain, Microsoft Agent Framework, or comparable AI agent frameworks.
Strong understanding of RAG, prompt engineering, context design, and AI evaluation.
Experience integrating AI applications with enterprise systems, APIs, microservices, and web interfaces.
Familiarity with cloud deployment, preferably AWS.
Understanding of secure software development, data privacy, and access management.
Strong collaboration, communication, and problem-solving skills.

Nice To Haves

Bachelor's degree with 10+ years of relevant AI/ML or software engineering experience.
Hands-on experience with Ask Sage (highly preferred).
Familiarity with NIST AI safety frameworks and responsible AI practices.
Experience implementing authorization-aware RAG, data filtering, and secure AI tool access.
Experience with AI evaluation, tracing, observability, monitoring, and optimization.
Knowledge of human-in-the-loop workflows, explainability, and AI governance.
Relevant cloud, AI/ML, or software engineering certifications.

Responsibilities

Design, develop, test, deploy, and maintain AI/ML applications, services, and agent-based workflows.
Build RAG solutions involving data ingestion, retrieval, grounding, and enterprise data integration.
Integrate LLMs and AI models with APIs, microservices, enterprise applications, and business workflows.
Develop scalable application components and APIs using Python.
Implement AI agents using LangChain, Microsoft Agent Framework, or similar technologies.
Conduct automated testing and AI evaluations for accuracy, relevance, safety, grounding, and performance.
Troubleshoot AI applications, optimize model performance, and support production deployments.
Implement secure AI practices, including access controls, authorization-aware retrieval, and sensitive data protection.
Collaborate with engineering, cloud, cybersecurity, DevSecOps, and product teams.
Develop AI safety and alignment policies to promote ethical, secure, and responsible AI systems.
Maintain technical documentation and reusable engineering components.