Software Architect, AI Applications

The role

You will lead the architecture and technical direction of the Revenue Harness agentic framework. This hands-on role involves building scalable agentic systems and guiding design decisions across teams.

What you will do

• Lead the architecture and technical direction of the Revenue Harness
• Define reference architecture and contracts between agents, tools, context, and models
• Embed in teams to contribute directly to design and code
• Set evaluation methodology, regression gates, and production monitoring
• Raise design quality and best practices through mentorship
• Drive adoption of coding agents and agentic workflows
• Build agent orchestration, planning, and reasoning loops
• Develop secure, extensible tool ecosystems
• Create retrieval pipelines using RAG, hybrid search, and knowledge graphs
• Manage multi-provider model routing, observability, cost, and latency

Required qualifications

• 10+ years of backend development
• Strong expertise in Java and modern frameworks such as Spring Boot
• Proven Staff or Principal-level impact across multiple teams
• Ability to lead through influence rather than authority
• Hands-on experience shipping production LLM applications, such as agents, tool calling, RAG, or structured generation
• Understanding of LLM failure modes
• Deep expertise in designing large-scale distributed systems, including asynchronous, event-driven, and streaming architectures
• Versatility in diving into unfamiliar codebases and switching context across teams
• Ability to communicate complex ideas clearly to diverse stakeholders
• Passion for mentoring
• Curiosity about the AI landscape
• Track record of driving adoption of AI-assisted development

Nice to have

• Experience with agent frameworks and protocols (e.g., MCP, Spring AI, LangChain/LangGraph) or with building an in-house equivalent
• Experience with LLM evaluation (LLM-as-judge, golden datasets, online monitoring), observability, and multi-provider routing
• Experience with vector databases, search infrastructure (e.g., Elasticsearch/OpenSearch), or knowledge graphs
• Familiarity with AI security concerns, including prompt injection, data leakage, and agent permission models
• Working knowledge of Python alongside a JVM stack
• Background in B2B SaaS, CRM, or revenue technology

About the company

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.