ZoomInfo is looking to solve the problem of building multi-agent systems that enable collaboration between agents and tools, and applying Generative AI to augment human and system intelligence.
Requirements
- Strong Python skills—able to prototype quickly and deliver maintainable, production-grade systems.
- Solid ability to explore datasets, form hypotheses, and execute projects that leverage data through enrichment, transformation, or generative AI techniques.
- Experience building LLM-powered and agentic systems using frameworks such as LangChain, LangGraph, or custom orchestration layers.
- Understanding of context retrieval, grounding, and compression techniques to optimize reasoning performance.
- Experience quantifying stochastic performance and designing evaluation metrics that measure prompt quality, reasoning depth, and user-perceived value.
- Familiarity with vector databases, embedding stores, and retrieval-augmented generation (RAG) architectures.
- Experience with cloud-native systems (AWS/GCP), containerization (Docker/Kubernetes), and modern observability tooling.
Responsibilities
- Build multi-agent systems that enable collaboration between agents and tools—implementing communication patterns, memory structures, and orchestration logic so agents can reason, plan, and act effectively.
- Use Generative AI to augment human and system intelligence, applying LLMs to automate data synthesis, decision support, and workflow optimization.
- Implement context engineering solutions to retrieve relevant information from internal data, MCP tool calls, and prior interactions—constructing focused contexts that improve reasoning accuracy.
- Design and implement evaluation frameworks to measure stochastic outcomes, providing visibility into how prompts, models, and agent architectures impact user value and reliability.
- Work with datasets—explore patterns, enrich or transform raw inputs, and apply generative or predictive methods to enable new product capabilities.
- Prototype and iterate on new agentic patterns—moving from idea to measurable impact through experimentation, A/B testing, and telemetry-driven improvement.
- Translate experimental models and reasoning patterns into scalable, observable, and cost-efficient production services.
Other
- A product-focused mindset—thinking in terms of user value and thriving in environments where specifications evolve and goals are outcome-driven.
- Experience contributing to platforms and reusable components that enable other teams to build AI-driven solutions.
- Strong communication skills, collaborative approach, and ownership mindset in complex, fast-moving projects.
- Ability to work in a hybrid environment
- Qualifications, skills, experience and/or training
