Forward Deployed Senior Data Scientist

About the Role

We are seeking an inquisitive Data Scientist to join our team, leveraging deep expertise in Artificial Intelligence and a keen understanding of complex Defense Acquisition challenges. Your primary focus will be to work with our proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help our government clients make more informed decisions. You will design, develop, and rapidly deploy scalable AI solutions that transform these insights into mission-critical capabilities. This role offers the opportunity to expand and grow data-driven research across Air, leading new areas to apply advanced analytics to drive strategic business and national security results.

This is a full-time position located in Arlington, VA, Pittsburgh, PA, or remote. This role may require up to 50% travel.

Responsibilities

• Develop AI/ML/DS systems to address defense problems.
• Develop new AI-based stack of technologies for particular customer needs.
• Create evaluation solutions for AI deployments.
• Lead the end-to-end execution of AI projects, ensuring alignment with strategic objectives and timely delivery.
• Work closely with partner teams, including AI research, data engineering, and software development, to deliver robust AI systems.
• Collaborate with AI leadership to define product and applications scope, translating high-level requirements into actionable technical plans and delivering AI platforms and solutions.
• Drive the development of scalable, AI-based platforms designed to support and power solutions for a diverse range of customers within the defense ecosystem.
• Champion the introduction of new AI innovations. Stay current with rapidly evolving fields of Artificial Intelligence, Large Language Models (LLMs), and agentic systems, and actively transfer this knowledge and best practices for implementation across the team.
• Mentor and guide other team members, fostering a culture of technical excellence, continuous learning, and high-impact work.
• Create agentic AI systems, using AI orchestrators and particular AI reasoning capabilities as tools.

Requirements

• U.S. Citizenship is required.

Skills

Required Skills

• Oversee the full lifecycle of AI projects within the Air AI ecosystem.
• Understanding of coding AI (such as Claude Code) and experience using it to scale up AI team deliveries.
• Ensure timely project delivery and strategic goal alignment.
• Collaborate with cross-functional teams (AI Research, Data Engineering, Software Development).
• Define robust software architecture for AI systems and project roadmaps.
• Translate high-level AI system requirements into actionable technical plans.
• Deliver production-ready AI solutions integrated with clients' data platforms and workflows.
• Drive the implementation of scalable AI/ML platforms.
• Maintain deep expertise in cutting-edge AI, including LLMs and agentic systems.
• Train models, build systems based on AI innovations.
• Champion innovation and best practices across the organization.
• Mentor and coach team members.
• Foster a high-performing culture of technical excellence and continuous growth.
• Demonstrate strong National Security domain knowledge.
• Excellent oral and written communication skills, capable of translating complex AI concepts for both technical and non-technical audiences.
• Highly organized problem-solver with a passion for great work and intolerance of mediocrity.
• Independent, driven, and motivated to roll up your sleeves and get the job done.
• Creative, out-of-the-box thinker with a passion for quality and rapid prototyping/deployment.

Desired Skills

• A strong publication record in top conferences in AI, ML, NLP, or decision science areas.
• Deep knowledge of LLM and Agentic system evaluation, experience in building evaluation systems.
• Experience in LLM post-training or fine-tuning.
• Experience with MLOps practices, including deployment, monitoring, and management of large-scale models in cloud environments (e.g., GCP, AWS, Azure).
• Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions.