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EverQuote

Lead-generation marketplace connecting consumers with insurers

AI Technical Lead – Principal Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • Deep, current, hands-on experience in artificial intelligence and large language models.
  • Experience fine-tuning open-weight models using methods such as LoRA, QLoRA, SFT, or DPO, and running the models independently rather than relying only on hosted APIs.
  • Experience owning a production large language model system, including reliable model serving, version pinning, rollbacks, and explaining cost changes.
  • Enterprise-level design and architecture experience, with a track record of leading and delivering large, ambitious projects.
  • Strong Python and Rust skills, and fluency with modern large language model serving, retrieval, evaluation, and monitoring.
  • Eight or more years of engineering experience, including senior or lead ownership of complex technical systems and hands-on machine learning or large language model work.
  • Hands-on fine-tuning and deployment of open-weight or open-source models in production.
  • Enterprise design and architecture experience for complex, high-reliability systems.
  • Ability to set technical direction and execute methodically.
  • Experience collaborating effectively across teams.

Responsibilities

  • Own the technical architecture, determine where the agent’s reasoning runs, select and package models, and decide how AI platforms connect to the system, validating decisions through testing.
  • Fine-tune open-weight models for the product and choose appropriately between tuning, retrieval, and prompting.
  • Deploy the agent and MCP server with reliable, fast, and affordable serving, including versioning and rollback capability.
  • Build programmatic evaluation sets, guardrails, and monitoring for quality, drift, cost, and speed.
  • Design data models and tools with the AI product lead, including request and response payloads, exposed reasoning, and trust signals.
  • Set engineering patterns and standards for the team, and document code and architecture.
  • Monitor inference costs and make trade-offs to sustain performance and affordability as usage grows.
  • Help publish the team’s code, architecture, and findings.
  • Mentor engineers and provide leadership with regular visibility into technical progress and risks.

About the Company

EverQuote

Lead-generation marketplace connecting consumers with insurers

EverQuote operates an online insurance marketplace that connects consumers with insurance providers. It helps individuals seeking policies for homes, cars, and families find and compare options through a digital platform. Users input personal details and insurance needs; the platform prequalifies them and matches them with suitable insurers in their area, enabling side-by-side comparisons so customers can choose the best option. Revenue comes from a lead-generation model in which insurers pay EverQuote for the leads generated through the platform. The company also uses interest-based advertising to show targeted ads based on collected user data. The goal is to make insurance shopping easier, faster, and more affordable by using technology to pair consumers with relevant insurance options and providers.

Company size
201-500
Company stage
IPO
Headquarters
Cambridge, MA
Founded
2010

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