Director of Applied Science and Engineering - Knowledge Graphs & AI

Role Overview: Outreach, the complete agentic AI platform for revenue teams, is seeking a Director of Applied Science and Engineering to lead the vision, strategy, and execution of the company's Knowledge Graph and contextual AI capabilities. As a senior leader, you will be responsible for combining technical expertise in knowledge representation, graph-based learning, and reasoning systems with building and scaling a high-performing team. Your role will involve owning the technical direction of a per-tenant contextual knowledge graph that captures various aspects of a customer's sales environment to drive business impact through applied science innovation. Key Responsibilities: - Define and own the multi-year technical roadmap for Outreach's Knowledge Graph platform, including entity resolution, temporal reasoning, graph-based learning, and contextual inference - Build, hire, and lead a team of applied scientists and research engineers, establishing team culture, research rigor, and career development frameworks - Drive the design of per-tenant knowledge graph schemas tailored to the sales execution domain and oversee pipelines for information extraction from unstructured conversational and document data - Lead the development of reasoning and inference layers over the knowledge graph to power next-best-action suggestions, deal risk scoring, coaching recommendations, and competitive intelligence - Direct research into graph-based models over heterogeneous graph structures to support downstream reasoning, retrieval, and recommendation tasks - Partner with leaders in Engineering, Product, Design, and Data to align science investments with product priorities and establish processes for moving from research to production deployment - Foster connections with the academic community through conference participation, publications, and strategic academic partnerships Qualifications Required: - PhD in Computer Science, Machine Learning, NLP, or a related field with a focus on knowledge representation and reasoning, graph neural networks, information extraction, or conversational AI - 10+ years of experience in applied science or machine learning, with at least 3 years in a people leadership role managing teams - Demonstrated track record of building and shipping knowledge graph, NLP, or graph ML systems at production scale - Deep expertise in knowledge graph construction, entity resolution, information extraction, graph neural networks, temporal reasoning, or recommender systems - Strong engineering fundamentals, proficiency in Python / Golang, and experience recruiting and developing top applied science talent - Executive communication skills with the ability to translate research concepts into business impact narratives - Comfort with defining the problem space and taking end-to-end responsibility for research and model development initiatives Additional Details: Outreach offers a competitive salary, annual vacation time, medical policy coverage, life insurance, diversity and inclusion programs, employee referral bonuses, and opportunities for personal and professional growth within the company. The company is an equal opportunity employer dedicated to building diverse teams and encourages applicants from historically marginalized groups to apply. Role Overview: Outreach, the complete agentic AI platform for revenue teams, is seeking a Director of Applied Science and Engineering to lead the vision, strategy, and execution of the company's Knowledge Graph and contextual AI capabilities. As a senior leader, you will be responsible for combining technical expertise in knowledge representation, graph-based learning, and reasoning systems with building and scaling a high-performing team. Your role will involve owning the technical direction of a per-tenant contextual knowledge graph that captures various aspects of a customer's sales environment to drive business impact through applied science innovation. Key Responsibilities: - Define and own the multi-year technical roadmap for Outreach's Knowledge Graph platform, including entity resolution, temporal reasoning, graph-based learning, and contextual inference - Build, hire, and lead a team of applied scientists and research engineers, establishing team culture, research rigor, and career development frameworks - Drive the design of per-tenant knowledge graph schemas tailored to the sales execution domain and oversee pipelines for information extraction from unstructured conversational and document data - Lead the development of reasoning and inference layers over the knowledge graph to power next-best-action suggestions, deal risk scoring, coaching recommendations, and competitive intelligence - Direct research into graph-based models over heterogeneous graph structures to support downstream reasoning, retrieval, and recommendation tasks - Partner with leaders in Engineering, Product, Design, and Data to align science investments with product priorities and establ