Counsel Health

Counsel Health

Talent Partner (Engineering & Product)

Boston · Full-time

Sponsorship not specifiedDetected 14 days ago
Full-Stack DevelopmentDevOpsMachine LearningOutbound SalesRecruitingLeadership

About the role

  • You know the difference between a great engineer and a good one, and you care deeply about getting that call right.
  • You bring that same rigor to Product, with enough depth to recognize strong product thinking when you see it.
  • This is a role for someone who moves fast and holds a high bar at the same time.

Responsibilities

  • Own hiring across Engineering and Product, from first sourcing touch to signed offer, with support from senior team members on the harder calls
  • Partner with hiring managers to understand what great looks like for each role and keep pipelines moving
  • Own Ashby data integrity for every requisition you touch
  • Some exposure to Product recruiting, or a clear hunger to build that muscle
  • You're curious by nature and genuinely into AI, building with it and forming real opinions on your own time
  • We are optimistic as we build the future of care delivery from first principles.
  • We optimize for the company, not functions.

Requirements

  • 3-5 years of full-cycle recruiting experience, with meaningful time in technical roles
  • Working knowledge of engineering skill sets across backend, frontend, full-stack, ML/AI, data, and DevOps, beyond keyword matching
  • A track record of sourcing outbound, not just running process on inbound

Nice to have

  • Comfortable in an ATS (Ashby experience a plus, not required)

Compensation

  • Competitive salary, bonus, and equity

Benefits

  • Exposure: Direct access to leadership at a company building at the edge of AI and healthcare
  • Compensation: Competitive salary, bonus, and equity

Company info

  • Direct access to leadership at a company building at the edge of AI and healthcare
  • We are clinicians 1st, technologists 2nd.

This listing is sourced directly from Counsel Health's careers page and normalized into a canonical job model.