Software Architect, AI Applications
Salary not listed • Tel Aviv • Full-time
Posted 23d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
Gong is seeking a Software Architect for its AI Applications group to lead the architecture and technical direction of the Revenue Harness, an agentic framework powering an AI teammate for revenue professionals. This hands-on role involves guiding design decisions and building scalable, extensible agentic systems on state-of-the-art AI technology. You will embed with teams, define reference architectures, and set quality and reliability standards for non-deterministic systems. The role focuses on making LLM behavior trustworthy, managing context at enterprise scale, ensuring secure agents, balancing quality/cost/latency trade-offs, and driving architectural clarity and speed in a rapidly evolving AI landscape.
Responsibilities
- Lead the architecture and technical direction of the Revenue Harness agentic framework.
- Guide design decisions and help build scalable, extensible agentic systems.
- Define the reference architecture and contracts between agents, tools, context, and models.
- Set the group's evaluation methodology, regression gates, and production monitoring.
- Drive adoption of AI-assisted development tools and workflows.
- Make LLM behavior trustworthy through structured outputs, tool-call validation, and fallbacks.
- Efficiently manage context at enterprise scale for millions of conversations, deals, and accounts.
- Enforce data boundaries, user permissions, and tenant isolation for secure agents.
- Balance quality, cost, and latency trade-offs through model selection, caching, and routing.
- Bring clarity to loosely defined cross-team problems and steer teams toward aligned patterns.
- Catch architectural gaps early and make pragmatic trade-offs for system evolution.
Requirements
- 10+ years of backend development experience, with strong expertise in Java and modern frameworks like Spring Boot.
- Proven Staff or Principal-level impact across multiple teams, with the ability to lead through influence.
- Hands-on experience shipping production LLM applications (agents, tool calling, RAG, structured generation) and understanding their failure modes.
- Deep expertise in designing large-scale distributed systems (asynchronous, event-driven, streaming architectures).
- Versatility in diving into unfamiliar codebases, switching context across teams, and spotting high-impact opportunities.
- Passion for mentoring and ability to communicate complex ideas clearly.
- Genuine curiosity about the AI landscape and a track record of driving AI-assisted development adoption.
- Experience with agent frameworks and protocols (e.g., MCP, Spring AI, LangChain/LangGraph) or building in-house equivalents is a plus.