Principal GenAI Scientist

Must Have Qualifications: Must have hands-on experience with machine learning transitioned into GenAI. Rag, Python- Jupyter, other Software knowledge, using agents in workflows, strong understanding of data. Preferred: Built AI agent, MCP, A2A, Graph Rag, deployed Gen AI applications to production. Interview Format: 1 Round, In-Person About the Role We are seeking a Principal GenAI Scientist to join our client’s AI/ML team in McLean, VA. This is a hands-on role focused on designing, building, and deploying next-generation Generative AI applications, AI agents, workflows, and advanced RAG/GraphRAG solutions. The ideal candidate has transitioned from traditional Machine learning into GenAI and has proven experience taking solutions into production. You will work closely with consulting teams, shadowing and knowledge-sharing, while also leading the development of new business use cases. This includes creating AI-driven solutions, collaborating with full-stack developers, and solving complex data science problems through the use of LLMs and advanced AI techniques. Key Responsibilities Lead the end-to-end machine learning lifecycle, including model development, CICD pipelines, deployment, and productionization. Develop and deploy GenAI solutions: AI Agents, Workflows, RAG/GraphRAG implementations, and domain-specific applications. Partner with full-stack developers to integrate data science models into full-stack applications. Collaborate with consulting partners, ensuring smooth knowledge transfer and project continuity. Connect and integrate with enterprise databases (e.g., Snowflake) to enable data-driven AI applications. Apply strong prompt engineering and experimentation techniques for effective LLM usage. Present technical concepts effectively through PowerPoint decks, telling a clear story to technical and business stakeholders. Must-Have Qualifications 3–4 years of experience in Data Science/Machine Learning, with 2+ years of hands-on GenAI experience. Strong experience with: • RAG/ GraphRAG • Python (Jupyter, libraries, frameworks) • Agents in workflows • Data handling and pipelines Proven experience deploying AI/ML models into production. Ability to build AI agents and integrate them into business workflows. Familiarity with MCP, A2A, MCB. GitHub portfolio showcasing relevant GenAI or ML projects (required). Preferred Qualifications PhD in Computer Science, Data Science, or related field (preferred but not required). Experience with deep learning frameworks and advanced ML techniques. Track record of building full production-grade GenAI applications. Experience with database access/integration (e.g., Snowflake, relational DBs). Nice-to-Have Strong knowledge of CICD for AI models. Prior software engineering background. Experience working in consulting or cross-functional project teams. Ability to mentor and guide junior AI/ML engineers.