Engineering Team Lead - Application Infrastructure

Gong 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 an Application Infrastructure Team Lead, you’ll spearhead the development of the core frameworks and services that power our entire ecosystem. In this role, you’ll sit at the vital intersection of application development and systems engineering, ensuring our platform remains resilient, high-performing, and developer-friendly as we scale.

If you are a technical heavyweight who loves Java but thrives on leading teams through complex data and infrastructure puzzles, this is your opportunity to build the foundation for our next phase of growth.

You’ll Own

• Team leadership & mentorship: Guiding a high-performing engineering team and fostering a culture of ownership and excellence.
• Core application infrastructure: Designing and maintaining mission-critical frameworks using Java and Spring Boot.
• Technical standards: Defining and enforcing the benchmarks for code quality, system performance, and security across the entire stack.
• Streaming & messaging pipelines: Owning the reliability and scalability of asynchronous communication using Kafka or SQS.
  
  

• Data layer optimization: Leading specialists to tackle challenges in high availability and performance across PostgreSQL, MongoDB, OpenSearch, and Redis.
• Distributed systems complexity: Designing robust pipelines for asynchronous communication and data streaming at scale.
• Architecture gaps: Bridging the gap between DevOps and Product teams to align infrastructure capabilities with evolving business needs.
  
  

• Engineering velocity: Providing the foundational building blocks that empower all product engineering teams to build faster and better.
• System reliability: Ensuring the high availability, scalability, and security of mission-critical systems.
• Technical culture: Driving a mindset of continuous improvement and technical excellence that resonates across the R&D organization.
  
  

• You are a seasoned leader with 8+ years of hands-on technical experience, with at least 2+ years of experience leading engineering teams in a fast-paced environment.
• You have deep, hands-on experience with Java & Spring Boot, building complex, large-scale server-side applications (this is a must).
• You possess deep knowledge in at least one of the following: PostgreSQL, OpenSearch, Redis, MongoDB, SQS, or Kafka, and you know how to lead engineers to get the best out of these tools.
• You are highly proficient with AWS services and understand how to leverage cloud infrastructure to build resilient systems.
• You can see the big picture, balancing the need for immediate delivery with long-term architectural health and scalability.
• You excel at communicating complex technical concepts clearly to both technical and non-technical stakeholders and at building consensus across teams.
• You hold a Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
• We operate in a flexible hybrid work model.