The posting, in Gong's own words
archived Oct 7, 2026Gong harnesses the power of AI to transform how revenue teams win. The Gong Revenue AI Operating System unifies data, insights, and workflows into a single, trusted system that observes, guides, and acts alongside the world’s most successful revenue teams. Powered by the Gong Revenue Graph, AI-powered intelligence, specialized agents, and trusted applications, Gong helps more than 5,000 companies around the world deeply understand their teams and customers, automate critical sales workflows, and close more deals with less effort. For more information, visit www.gong.io. At Gong, you will join a company built on innovative products, ambitious goals, and passionate people. We are shaping the future of revenue intelligence and we want people who are excited to build what comes next. You will work with a team that dreams big, moves fast, and cares deeply about the craft and about each other. Here, transparency and trust are core to how we operate, and every person has the opportunity to make a visible impact. If you want to grow, stretch, and do work that truly matters, Gong is the place to do the best work of your career. As a Senior Backend Engineer on Gong’s Agentic team, you will build and operate production-grade AI agents that interact directly with Gong’s customers. You will design and implement the backend systems that enable these agents to understand customer requests, reason over context and data, interact with tools and APIs, and take meaningful actions on behalf of customers. This is a new, high-impact team focused on building customer-facing agentic product experiences. You’ll work extensively in the agentic AI space, designing and building AI-powered applications that communicate with customers and solve real-world problems. The systems you build will combine LLMs, agents, tools, APIs, business logic, and Gong’s data to deliver useful and reliable customer experiences at scale.
You’ll Own:
Customer-Facing Agent Development: Designing, building, and operating production-grade AI agents in Python that interact directly with customers and help them accomplish real-world tasks. Agent Behavior and Workflows: Building multi-step agentic workflows that understand customer intent, maintain context, reason over information, use tools, call APIs, and take actions on behalf of customers. Product Integrations: Connecting agents to Gong’s APIs, data, internal services, and external systems so they can retrieve information and perform meaningful actions as part of the customer experience. Production Reliability: Building robust agent applications that handle failures, retries, timeouts, unexpected inputs, and other real-world edge cases while serving live customer traffic. Agent Evaluation and Improvement: Measuring and improving agent quality using production data, offline and online evaluations, regression testing, experimentation, and customer feedback. End-to-End Backend Ownership: Taking ownership of the backend systems behind agentic product experiences, from design and implementation through deployment, operation, and continuous improvement.
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You’ll Solve:
Customer Interaction Complexity: Building agents that can understand customer intent, maintain context across conversations, reason over information, and take the right actions across complex workflows. Agentic Application Complexity: Designing applications where agents interact with tools, APIs, data, business logic, and external systems across multi-step workflows. AI System Reliability at Scale: Ensuring customer-facing agents remain reliable, observable, debuggable, and safe as usage scales across customers and products. Product and Engineering Tradeoffs: Balancing agent flexibility, product requirements, latency, reliability, cost, and safety when building real-world AI applications.
You’ll Impact:
Customer Experience: Building AI agents that directly interact with Gong’s customers and help them accomplish meaningful tasks faster and more effectively. AI-Powered Product Experiences: Turning emerging agentic capabilities into reliable, scalable product experiences used by real customers. Production AI Adoption: Bringing AI agents from experimentation into robust production applications that operate reliably at scale. AI Application Quality: Establishing strong engineering practices for building, evaluating, deploying, and continuously improving AI-powered applications in production. How You’ll Succeed Here 7+ years of backend engineering experience (Python) , with strong system design and application development expertise. Strong analytical and problem-solving skills, with the ability to debug and resolve complex technical issues efficiently. Hands-on experience designing, building, and operating AI agents or agentic applications in production, including orchestration, tool usage, context and memory management, and multi-step workflows. Experience building production applications with tools like LangChain, LangGraph, ADK, or similar agent orchestration frameworks. High proficiency in Python for building production-grade AI applications and backend services. Experience integrating AI-powered applications with APIs, databases, internal services, and external systems. Experience building backend applications and services in distributed systems. Strong analytical skills and the ability to reason about complex, evolving AI-driven applications. Experience with cloud platforms and scalable architectures. Excellent communication skills and a strong product mindset, with experience working closely with product and engineering teams. *We operate in a flexible hybrid work model.