About the job
At Gong, we leverage cutting-edge AI technology to revolutionize the way revenue teams achieve success. Our Gong Revenue AI Operating System integrates data, insights, and workflows into a cohesive system that observes, guides, and collaborates with the world's leading revenue teams. With over 5,000 companies globally benefiting from the Gong Revenue Graph, our AI-driven intelligence, specialized agents, and trusted applications empower organizations to gain deep insights into their teams and customers, automate essential sales processes, and close deals with increased efficiency. To learn more, visit www.gong.io.
Joining Gong means becoming part of a visionary company that values innovative products, ambitious objectives, and a passionate workforce. We are at the forefront of shaping the future of revenue intelligence, and we seek individuals who are eager to contribute to what comes next. Our team is characterized by bold aspirations, rapid progress, and a commitment to excellence. Here, transparency and trust are fundamental, and each employee has the chance to make a significant impact. If you are looking to grow, challenge yourself, and engage in meaningful work, Gong is where you can achieve the pinnacle of your career.
We are in search of an Engineering Team Lead who will oversee the foundational infrastructure framework that empowers all Gong engineering teams to build, deploy, and safely operate AI agents in production. You will be instrumental in creating the "operating system" for AI at Gong, focusing on agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. Leading a high-impact team of 3-4 engineers, you will define the runtime and platform that shapes the future of autonomous enterprise intelligence.
Your Responsibilities Include:
- Agentic Framework Architecture: Design and develop Gong’s internal agentic framework using industry-standard tools such as LangChain, LangSmith, ADK, and other relevant ecosystems.
- Evaluation and Quality Systems: Establish evaluation frameworks and workflows for AI agents, which encompass offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
- Team Leadership & Mentorship: Guide a team of 3-4 senior engineers, fostering a culture of technical excellence and managing end-to-end project delivery in a fast-paced environment. Expect to spend around 50% of your time hands-on, architecting core systems and reviewing code, while the other 50% will be dedicated to team leadership, mentoring engineers, and collaborating with cross-functional stakeholders.
- Observability, Monitoring, and Guardrails: Equip the organization with robust observability capabilities for AI agents, including tracing, logging, and monitoring.
