Salary
$200k – $230k per year
Location
Remote (likely United States)
Seniority
Staff
Employment
Full-Time
First seen by Alion on Nov 1, 2026.
Overview
Company
Impact
Profile match
Anzen does the work inside every policy transaction — quote, renewal, endorsement, binding — across the systems you already run.
Backed by Redstone, MS&AD VENTURES, Sandbox Industries
Anzen was founded by former insurance and tech executives who’ve collectively scaled three unicorns. Backed by leading investors like Andreessen Horowitz (a16z) and Madrona, we’re on a mission to transform how companies choose and understand commercial insurance using AI.Commercial insurance today runs on emails, PDFs, and lengthy underwriting cycles — often taking weeks to secure coverage. Anzen is building the world’s first AI insurance platform for brokers, radically improving how they manage submissions, select markets, and generate quotes for their clients.We've built a team from top universities, with experience scaling products at Google, Uber, Lyft, Oracle, and startups founded by the best investors in the world, and are continuing to scale our team in Mexico, Canada, and the United States.You will build our core technology to ensure it can scale to hundreds of millions of dollars in insurance policies and use ML to help insurance underwriters be 5-10x more effective. Responsibilities
- Partner with Design & Product to translate fuzzy broker pain points into concrete, AI capabilities that perform equally or better than human experts.
- Own the full ML lifecycle from framing business problems into research problems, evaluating results and rolling them out with the appropriate infrastructure.
- Architect production‑grade systems that marry real‑time inference with human‑in‑the‑loop review and comply with strict privacy & audit requirements.
- Elevate engineering quality, driving technical roadmaps and championing best practices
- Mentor our Engineering team and help define Engineering culture at Anzen.
- 8+ years building data‑intensive or ML‑driven backend systems
- Production mindset: you’ve shipped business critical models with measurable business impact (latency, cost, ROI).
- Broad ML toolbox, from classic ML (especially NLP) to GenAI
- Strong backend fundamentals: distributed systems, streaming data pipelines
- Fluency in Python and/or TypeScript in a production environment.
- Startup DNA: thrive in ambiguity, bias to action.
Originally posted on Himalayas
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