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Jerry.ai is a pre-IPO insurtech startup that has raised $240M and achieved profitability with 5M+ customers. The company pioneered early adoption of generative AI to automate customer interactions, handling over 50k chats per month with >70% automation of inbound sales and service requests.
You will lead the development and scaling of Jerry's AI platform, sitting at the intersection of product, engineering, and applied AI. The role owns the end-to-end strategy for customer-facing agentic AI products that leverage LLMs, agents, and internal APIs. Currently, AI prompts and systems are fragmented across six separate locations with no unified platform or clear ownership. You will consolidate this infrastructure and establish it as a single source of truth.
Key responsibilities include:
- Lead end-to-end development of the AI platform and customer experiences from roadmap through rollout
- Partner with engineering to design prompt strategies, evaluation frameworks, and guardrails balancing latency, cost, and accuracy
- Serve as technical translator between engineering and broader organization, establishing AI best practices and platform standards
- Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation
- Collaborate with OpenAI partners to evaluate and deploy next-generation voice models and workflow automation capabilities
- Shape how modern LLM systems, human-in-the-loop feedback, and computer-use agents redefine the insurance and automotive industries
You report directly to the COO and own one of the company's most important growth levers. The organization has a flat structure with ambitious goals and significant opportunities for career acceleration.
Ideal candidates have 3+ years in technical roles such as forward-deployed engineering or technical product management at fast-paced startups. You are deeply passionate about AI systems, comfortable with technical conversations about API design and system architecture, and have a track record of turning complex strategic ideas into scalable, production-grade products. SQL fluency and data-driven decision-making are expected.
