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Salary: USD 180,000 - 220,000 / annual
Kalepa is building professional-grade AI systems for the insurance industry, a $7T global sector. The company creates software that can read, reason, decide, and act within real workflows, augmenting insurance professionals in underwriting, claims, pricing, operations, and distribution. Products are already in production with leading insurers, and the company is backed by investors including IA Ventures and Inspired Capital, with a team drawn from Facebook, Palantir, Google, Amazon, McKinsey, Mastercard, and Uber.
You will own full-cycle recruiting for Engineering, Product, and Design functions, building the hiring engine for Kalepa's next stage of growth. This is a strategic and operational role that shapes processes, tools, and employer brand.
Key responsibilities include:
- Own full-cycle recruiting for Engineering roles: intake, sourcing, interviews, offer, and close
- Run intake with hiring managers to develop clear scorecards and search strategies
- Source and build pipelines for passive, hard-to-find technical and AI/ML talent
- Bring market and compensation intelligence into hiring plans; lead offer negotiation and closing
- Build and improve interview processes: kits, scorecards, structured debriefs
- Act as a strategic partner to company leaders and hiring managers, ensuring hiring goals are met with top-tier candidates
- Strengthen Kalepa's employer brand in the engineering and AI community
The role is hybrid in New York, with a global team across 10+ languages. The company invests in regional meetups and annual global offsites.
Requirements:
- 5+ years of full life-cycle technical recruiting experience
- Track record hiring backend, infrastructure, full-stack, or ML/AI engineers
- Experience partnering directly with engineering leaders on intake and closing
- Strong independent sourcing skills, not just inbound processing
- Fluency in Greenhouse (or comparable ATS) and modern sourcing tools (Juicebox, Metaview, Seekout)
- Ability to own a full requisition load with minimal oversight
- Creative approach to experimenting with new tools to identify and engage top engineers
- Self-critique and transparency about what's working and what's not
- Experience nurturing pipelines over time and maintaining candidate relationships
Plus factors:
- Experience recruiting for AI/ML or LLM-focused roles
- Experience building a recruiting function from early stage
- Insurtech, fintech, or regulated B2B SaaS recruiting experience
