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Jerry.ai is a pre-IPO insurtech startup that has raised $240M, serves 5M+ customers, and is profitable. The company pioneered early adoption of generative AI in insurance, building proprietary infrastructure to automate sales and service conversations before off-the-shelf platforms existed.
You will lead the technical product strategy for Jerry's customer-facing Agentic AI platform, which leverages LLMs, agents, and internal APIs. You'll report directly to the COO and own one of the company's most important growth levers. Your scope spans two layers: maintaining the current AI platform's operational excellence while architecting its future state.
In your first months, you'll learn the prompt engineering workflow by writing and updating prompts, understanding how various tech stacks (Propelix, Botly, CRM, GitHub, Replit) interact, and identifying bottlenecks. You'll then transition to owning platform strategy:
- Prompt Consolidation: Define and execute the strategy for migrating prompts from six separate locations onto a unified platform. Sequence the work, align engineering, data, operations, and other teams, and drive execution.
- Chatbot Prioritization: Own the technical prioritization queue, keeping the team coordinated and moving without adding process overhead.
- Emerging Technology Decisions: Monitor voicebot and computer use capabilities closely to identify when they cross the investment threshold. Own the OpenAI relationship and Jerry's presence in the ChatGPT store, bringing strategic perspective to AI investment decisions.
You are a technologist who lives and breathes AI, reads release notes when new models drop, and has built custom workflows. You're a systems thinker comfortable with technical conversations about API design and architecture, translating complex concepts for any audience. You're an experimenter who thinks in terms of what's possible and constantly tinkers with new capabilities. You're data-driven, familiar with SQL, and comfortable diving into data to validate hypotheses. You're pragmatic, navigating technical tradeoffs and leading by example when implementing AI platform standards.
Ideal candidates have 3+ years in technical roles like forward deployed engineering or technical product management at fast-paced startups, with passion for AI systems including modern LLMs, and a track record of turning complex strategic ideas into scalable, production-grade products.
