Q

Qumis

AI-powered policy analysis for insurance

Founding Staff AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-time$150k - $250k /yr

About the Job

Requirements

  • At least 6 years of experience building and deploying production machine learning systems, focused on natural language processing, document intelligence, or unstructured data.
  • A strong track record shipping machine learning models into production, including API design, observability, iteration, and scaling.
  • Deep experience with retrieval-augmented generation pipelines, multi-step large language model workflows, and vector databases such as Pinecone, Weaviate, or Qdrant.
  • Comfort working with complex documents such as insurance policies and contracts, including parsing, optical character recognition, clause-level segmentation, and normalization.
  • A strong software engineering background, including full-stack development, Docker containerization, and DevOps or MLOps best practices.
  • Ability to design secure, compliant systems in regulated environments such as insurance, legal, healthcare, or finance.
  • Experience architecting agentic workflows and AI-native products beyond simple chatbot interfaces.
  • A product-first approach to building models that solve user problems and working closely with cross-functional teams.
  • A hands-on, ownership-oriented approach and ability to work in fast-paced, zero-to-one environments.

Responsibilities

  • Build and ship production AI features end-to-end, from research and development through SaaS integration, observability, and iteration.
  • Design and deploy document-understanding systems, including retrieval-augmented generation pipelines, clause segmentation, summarization, and risk detection.
  • Create scalable APIs for real-time coverage analysis, comparisons, and recommendations in a SaaS user interface.
  • Engineer data workflows for optical character recognition, PDF ingestion, parsing, normalization, and embedding generation.
  • Own evaluation and observability, including automated accuracy pipelines and human-in-the-loop systems to maintain trust and reliability.
  • Design explainable workflows that help legal, claims, and compliance professionals understand AI outputs.
  • Collaborate with designers, product managers, and domain experts to translate insurance workflows into AI-powered systems.
  • Set technical direction and shape infrastructure, tooling, and the AI product roadmap.

About the Company

Qumis

AI-powered policy analysis for insurance

Qumis provides an AI-powered platform that helps insurance professionals analyze and interpret complex policy language, targeting brokers, claims leaders, attorneys, and risk managers. It uses a centralized Document Vault and a Prompt Library to organize documents and standardize reviews, with AI-assisted analysis that supports decision-making while requiring human input. The system emphasizes data security with a private encrypted vault and does not use client data for AI training, differentiating itself with a human‑in‑the‑loop workflow and leadership from insurance and fintech veterans. Its goal is to scale its AI capabilities, grow its U.S. insurance customers, and keep improving policy interpretation, claims handling, and underwriting.

Company size
11-50
Company stage
Seed
Total funding
$6.8M
Headquarters
Chicago, IL
Founded
2022

Recently Posted Jobs

Explore more opportunities at Qumis

See more jobs