About the Role
Design and build the knowledge infrastructure that powers Gallup’s most ambitious AI initiatives. As an AI research scientist at Gallup, you will shape AI systems built on some of the richest behavioral datasets in the world. If you bring the rigor of a researcher and the instincts of a systems thinker, and you want to design what doesn't yet exist, you'll thrive in Gallup Labs.
About Gallup Labs
Gallup Labs is the internal research and incubation engine at Gallup, where the world's most important questions about human behavior meet at the intersection of research and technology. We work on problems that don't have clear road maps: building novel knowledge architectures from decades of behavioral data, designing AI systems that surface talent signals and prototyping the next generation of human-centered intelligence tools for a variety of markets.
What You’ll Do
- Design, prototype and evaluate applied AI systems for knowledge representation, retrieval and agentic reasoning
- Build knowledge architectures that combine knowledge graphs, vector databases, RAG pipelines and hybrid retrieval approaches for behavioral and scientific data
- Own core retrieval infrastructure, including ontology design, schema design, embeddings, indexing, LLM-based extraction, entity resolution, graph storage and query patterns
- Translate ambiguous research questions into clear technical approaches, experiments and working systems
- Create evaluation frameworks for reasoning quality, retrieval accuracy, scalability and real-world impact
- Partner with researchers, product leaders and technologists to integrate knowledge systems into larger AI workflows and communicate architectural decisions clearly
- Stay current on applied AI research and identify techniques that can strengthen Gallup’s AI capabilities
What Makes You Stand Out
- Entrepreneurial mindset: You are relentlessly curious about what could exist, spot unmet needs and take ownership of turning technical possibility into systems that create measurable value.
- Systems thinking: You instinctively see how technical components interact, anticipate failure modes and design and test architectures that are resilient and adaptable.
- Architectural creativity: You evaluate trade-offs across graph, vector and hybrid systems and are energized by inventing new combinations when standard approaches fall short.
What You Need
Required
- Bachelor’s degree in computer science, data science, applied mathematics, cognitive science or a related quantitative field, plus two years of experience, or an advanced degree in ML, NLP, information science or computational social science
- Experience building applied AI systems, knowledge architectures or advanced data systems in industry, research or comparable settings
- Strong hands-on experience with knowledge graphs, including ontology and schema design, extraction pipelines, graph storage and traversal
- Experience using LLMs for structured extraction of entities, relations and attributes
- Experience designing advanced retrieval systems and evaluating reasoning and extraction quality
- Strong Python skills and fluency with modern AI development stacks such as LangChain, LangGraph or LlamaIndex
- A commitment to working on-site at Gallup’s Washington, D.C., office at least three days per week
Preferred
- Experience turning research ideas into production-ready AI systems
- Hands-on experience with agentic workflows, including multi-step reasoning, tool use and planner/executor patterns
- Ability to build lightweight service layers and interfaces, such as FastAPI, to inspect and evaluate extraction and retrieval quality
- Advanced experience with entity resolution, graph learning or hybrid database architectures that combine graph, vector and relational systems
- Experience with major cloud AI ecosystems such as Azure OpenAI, AWS Bedrock, GCP Vertex or comparable self-hosted solutions