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Gong is seeking a Prompt Engineer to architect and optimize advanced AI systems that power its Revenue AI Operating System. This role goes beyond basic prompt design to focus on building sophisticated multi-agent workflows that enhance how revenue teams operate.
Key Responsibilities:
- Design and develop highly optimized prompts for diverse applications including text generation, question answering, sentiment analysis, rating, and summarization
- Continuously analyze and iterate on prompts and agent behaviors using performance metrics, evaluation frameworks, and user feedback to ensure reliable, high-quality outputs
- Conduct systematic experiments to test new prompting techniques, benchmark agentic workflows, and integrate the latest advancements in NLP and Generative AI
- Create clear, structured documentation of prompt architectures, system behaviors, and testing methodologies for both technical and non-technical audiences
- Solve complex challenges around LLM reasoning and agent logic to enable accurate, context-aware assistance at scale
- Bridge user requirements and technical execution by designing prompts and agent architectures that improve end-user experience
- Reduce hallucinations, improve output consistency, and ensure agentic systems perform reliably across millions of dynamic customer interactions
- Stay current with rapidly evolving LLM and AI research landscapes
The role will directly impact thousands of companies by empowering them to transform how they interact with customers and automate critical workflows. You will collaborate closely with product teams, data scientists, and engineers to shape the future of agentic AI.
Requirements:
- Proven experience as a Prompt Engineer, AI Engineer, or similar role focused on LLMs and Generative AI
- Hands-on experience designing and building architectures for AI agents and multi-agent workflows (e.g., LangChain, AutoGen, or similar frameworks)
- Deep understanding of modern AI approaches including Retrieval-Augmented Generation (RAG), few-shot prompting, chain-of-thought reasoning, and LLM evaluation methods
- Familiarity with natural language processing (NLP) concepts and ability to stay current with latest AI research
- Strong analytical skills with proven track record of designing experiments, analyzing prompt performance, and iterating based on data
- Excellent communication skills and ability to collaborate effectively with cross-functional teams (Product, Data Science, Engineering) and explain complex concepts clearly
