Lead Data Scientist - Knowledge Retrieval

About the role

The Lead Data Scientist will provide visionary technical leadership to a team of data scientists and AI engineers, driving the end-to-end development and deployment of cutting-edge Artificial Intelligence solutions for our National Security clientele. This role is key to building a strong culture of advanced agentic search, deep research, retrieval, and AI, and to creating scalable AI platforms for the wider AI and Data Science community.

As a hands-on technical leader, you will apply deep expertise in Artificial Intelligence and a keen understanding of complex Defense Acquisition challenges. Your primary focus will be working with proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help government clients make more informed decisions. This involves designing, developing, and rapidly deploying scalable AI solutions that transform insights into mission-critical capabilities.

You will also expand and grow data-driven research across Air, leading new areas to apply advanced analytics for strategic business and national security results. The role includes building and leading the development of advanced agentic search, knowledge retrieval, and deep research systems that provide deep conversational knowledge explorations, robust problem-solving, accurate question answering, and other search, recommendation, and discovery capabilities.

This is a full-time position located in Pittsburgh, PA, with up to 10% travel required.

Responsibilities

• Drive the architecture and development of the 'Air Brain,' a complex, multi-modal intelligent agent system for knowledge retrieval and deep research, serving as the central nervous architecture for powering agentic AI search, deep research, RAG, and knowledge graph systems across the Air Enterprise Readiness platform.
• Define the multi-year technical roadmap for AI initiatives, turning vague business challenges into concrete, scalable research and product goals.
• Mentor Senior-level engineers and build high-performing teams that consistently deliver state-of-the-art (SOTA) results.
• Drive consensus across disparate groups such as Data Science and AI, Product, Forward Deployed AI, and Engineering to ensure AI deployments are technically sound, commercially viable, and responsible.
• Act as the authority on scientific breakthroughs and model strategy, ensuring core architectures, training methodologies, and data ecosystems are robust, cost-effective, and future-proofed against the rapidly evolving AI landscape.
• Lead the end-to-end execution of large-scale AI projects, ensuring alignment with strategic objectives and timely delivery.
• Develop advanced agentic search, knowledge retrieval, and deep research systems.
• Expand data-driven research and advanced analytics for strategic business and national security results.
• Design and deploy Agentic AI systems capable of deep conversational knowledge explorations, robust problem-solving, and accurate question answering from proprietary datasets.
• Serve as the primary Individual Contributor (IC) and technical lead for complex AI/ML/DS projects, taking deep ownership from ideation to production deployment.
• Act as the domain expert in AI Search Science (ranking, query understanding, agentic search, deep research, embedding models, etc.), driving the application and development of state-of-the-art methods.
• Collaborate with partner teams, including AI research, data engineering, and software development, to define robust software architecture, set project roadmaps, and manage technical execution.
• Work closely with the Product team to define product scope, translate high-level requirements into actionable technical plans, and deliver market-ready AI solutions integrated with client data platforms and workflows.
• 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, staying current with advancements in Artificial Intelligence, Large Language Models (LLMs), and agentic systems, and transferring this knowledge for implementation across the team.
• Mentor and guide junior and senior team members, fostering a culture of technical excellence, continuous learning, and high-impact work.
• Nurture a robust AI culture within the team by leading technical discussions, conducting internal workshops, and promoting best practices in model development, experimentation, and MLOps.
• Demonstrate strong leadership to align the team's AI strategy with overall business and client needs, translating complex technical concepts into strategic business impacts for leadership.

Requirements

• U.S. Citizenship is required.
• Minimum of 7 years of professional experience working as a Data Scientist in an industry setting.
• Experience overseeing the full lifecycle of large-scale AI projects.
• Understanding of coding AI (such as Claude Code) and experience using it to scale up AI team deliveries.
• Expertise in designing and implementing Retrieval-Augmented Generation (RAG) architectures and complex indexing strategies for proprietary, large-scale, heterogeneous datasets.
• Expertise in fine-tuning multi-modal embedding models.
• Proven ability to leverage state-of-the-art LLMs, multi-modal embedding models, vector databases, and knowledge graph systems to build production-ready knowledge retrieval, conversational AI search, and Deep Research systems.
• Practical experience building hybrid knowledge retrieval systems that combine advanced techniques like embedding models, knowledge graphs, and traditional methods (e.g., BM25), utilizing novel paradigms such as GraphRAG, RAG-RL, and other advanced retrieval strategies.
• Deep knowledge of and practical experience with ranking and reranking models, including multi-tower, bi-encoder, and cross-encoder architectures, specifically within search and knowledge retrieval systems.
• Expert proficiency in developing and deploying multi-agent AI systems and reasoning frameworks (e.g., ReAct, Chain-of-Thought) for complex knowledge exploration, robust problem-solving, and decision support within search and retrieval contexts.
• Ability to ensure timely project delivery and strategic goal alignment.
• Experience collaborating with cross-functional teams (AI Research, Data Engineering, Software Development).
• Ability to define robust software architecture for large-scale AI systems and project roadmaps.
• Experience translating high-level product requirements into actionable technical plans.
• Track record of delivering production-ready AI solutions integrated with clients' data platforms and workflows.
• Experience driving the implementation of scalable AI/ML platforms.
• Maintain deep expertise in cutting-edge AI, including LLMs and agentic systems.
• Experience training models and building systems based on AI innovations.
• Ability to champion innovation and best practices across the organization.
• Experience mentoring and coaching team members.
• Ability to foster a high-performing culture of technical excellence and continuous growth.
• Help leadership align AI strategy effectively with client needs.
• Experience creating agentic AI systems using AI orchestrators and reasoning capabilities.

Qualifications (Desired)

• A strong publication record in top conferences in AI, ML, NLP, and decision science areas.
• Deep knowledge of LLM and Agentic system evaluation, with experience building evaluation systems.
• Experience in LLM post-training or fine-tuning.
• Strong National Security domain knowledge.
• 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.