Generative AI Engineer

About the Company

MeeBoss helps job seekers and hiring teams make direct, relevant career connections.

About the Role

MeeBoss is sharing this active opportunity on behalf of the hiring company. This role involves leading or contributing to cross-functional teams to develop and operationalize AI solutions for enterprise-scale and Government applications.

The position requires applying modern engineering techniques to design, deploy, and maintain end-to-end AI workflows, including model training, inference, and performance monitoring.

Responsibilities

• Design, develop, train, test, deploy, and maintain AI and machine learning models for enterprise-scale and Government applications.
• Develop and operationalize production of AI/ML solutions, ensuring models and supporting systems are reliable, scalable, maintainable, and appropriate for mission requirements.
• Collect, clean, transform, analyze, and prepare structured and unstructured data for AI/ML model development, training, testing, and evaluation.
• Evaluate potential AI technologies, models, tools, frameworks, and architectures and recommend solutions appropriate for complex Federal Government and cybersecurity use cases.
• Apply AI and machine learning techniques to solve real-world business, cybersecurity, engineering, analytics, and operational problems across a large enterprise environment.
• Develop and support Generative AI and Large Language Model (LLM) solutions, including model configuration, system prompts, classifiers, fine-tuning, content moderation, safety filters, and other model controls.
• Evaluate AI-generated outputs for accuracy, factuality, grounding, reliability, bias, helpfulness, honesty, and overall model performance before outputs are incorporated into efforts.
• Design and execute AI/ML model evaluation and validation methodologies, including benchmark testing and comparative evaluation of model outputs.
• Perform and support AI red-team testing to identify weaknesses, unintended model behaviors, bias, security vulnerabilities, and other risks associated with AI-generated outputs.
• Implement mechanisms and controls to improve the factuality and grounding of AI/LLM outputs, including system-level instructions, source attribution, content controls, and appropriate response behavior when information is incomplete, contradictory, or uncertain.
• Produce technical documentation, analysis, recommendations, briefings, and other materials that clearly communicate AI architecture, model performance, risks, controls, and recommended courses of action to both technical and non-technical stakeholders.
• Deliver Government-owned AI-related technical artifacts developed under the program, including applicable models, model weights, algorithms, configurations, documentation, data models, source code, and supporting technical components.
• Adapt and integrate diverse AI model architectures, including computer vision systems, natural language processors, audio processors, large language models (LLMs) and multi-modal frameworks to address complex mission-critical challenges.
• Monitor and maintain AI products through systematic identification of performance degradation and computational inefficiency and address these challenges through regular fine-tuning to ensure continued alignment with evolving mission needs and organizational goals.
• Maintain knowledge of current AI research and adapt emerging techniques to intelligence applications.
• Test and evaluate AI solutions against mission requirements and produce actionable recommendations.

Qualifications

• Bachelor’s degree in engineering, Computer Science, a related field, or equivalent practical experience.

Required Skills

• Minimum of 5 years of experience in relevant fields including IT security, data science, or software engineering, design, development, or deployment of AI or machine learning systems in enterprise or Government environments.
• Experience working on data science, machine learning, or AI projects, either through internships, research projects, or professional roles.
• Experience building, training, and deploying machine learning models and AI systems in a production environment.
• Experience collaborating with cross-functional teams, including data scientists, software developers, and domain experts.
• Experience in data collection, cleaning, and analysis techniques to prepare datasets for AI modeling.
• Experience applying AI solutions to real-world problems in various enterprises and domains such as large corporations and Government agencies similar in size/scope to GSA, IRS, DoD or VA.
• 5 years of experience with software development using Python or similar coding languages.
• Experience architecting AI systems on cloud platforms (e.g., AWS, Google Cloud Platform).

Preferred Skills

• Preferred: Master’s or PhD in AI, Computer Science, or related technical field.
• Preferred: Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
• Preferred: Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
• Preferred: Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
• Preferred: Track record of troubleshooting live, high-traffic systems during critical windows.

Pay range and compensation package

• Job title AI Engineer
• Company MeeBoss
• Location Reston, VA
• Compensation Full-time, Contract