Job Summary We are seeking a Senior-level AI/ML Engineer to design, develop, and deploy advanced artificial intelligence and machine learning solutions in support of mission-critical government programs. This role requires deep expertise in architecting scalable, high-performing AI systems on cloud platforms, integrating AI/ML models with enterprise systems, and leveraging big data processing to drive intelligent outcomes. The ideal candidate brings hands-on experience with cloud-based AI platforms, advanced machine learning techniques, and Responsible AI practices, and thrives in a collaborative, fast-paced technical environment. Responsibilities • Design, develop, and deploy scalable AI/ML solutions on cloud platforms. • Architect high-performing AI systems for predictive analytics, natural language processing, and computer vision applications. • Implement and manage AI/ML pipelines and tooling in cloud environments. • Integrate AI/ML models with existing enterprise and cloud-based systems to ensure seamless operations. • Apply advanced machine learning techniques and big data processing to enhance model performance. • Adhere to Responsible AI (RAI) policies and develop metrics to evaluate AI solution effectiveness. • Collaborate with cross-functional teams to identify opportunities for AI/ML adoption and integration. • Stay current with emerging AI/ML technologies, tools, and industry best practices. Qualifications Required • Active TS/SCI clearance. • Bachelors or Masters degree in Computer Science, Information Technology, Management Information Systems, or a related STEM field. • 6–10 years of experience in AI/ML development and deployment. • Proven experience in designing and implementing AI/ML solutions and cloud-based pipeline tools. • Advanced expertise in architecting scalable, high-performing AI systems for NLP, computer vision, and predictive analytics. • Extensive experience with cloud AI platforms such as Azure Machine Learning, AWS SageMaker, or Google Vertex AI. • Strong background in big data processing and advanced ML techniques. • Demonstrated ability to integrate AI/ML models with enterprise systems and cloud environments. • Deep proficiency in machine learning programming languages such as Python or R. • In-depth knowledge of AI cloud tools and capabilities. • Understanding of Responsible AI (RAI) principles, metrics, and evaluation methodologies. • Relevant certifications such as: • Azure Solutions Architect • AI Engineer Associate (or equivalent) • AWS Certified Machine Learning • Security+ Desired • Experience with containerization and orchestration technologies (Docker, Kubernetes). • Knowledge of DevOps practices and CI/CD pipelines. • Familiarity with data visualization tools and techniques. • Strong problem-solving skills and ability to perform effectively in a fast-paced environment.