Founding Sourcing Manager

Scalis LLC; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Calibratr is building AI-native, evidence-based recruiting pods for fast-scaling AI startups, with a focus on healthcare applications. The role leads sourcing and calibration across client engagements, building teams, tooling, and quality bars that enable a small pod to out-perform larger firms.

You’ll own the sourcing workflow with tools like Claude, Exa, and Ashby, drive high-bar searches, and calibrate talent pipelines for senior and staff positions while coaching contract sourcers and

Qualifications

• Experience leading sourcing teams for senior and staff roles.
• Ability to build and enforce a high-quality sourcing bar.
• Proven track record in evidence-based recruiting workflows.

Responsibilities

• Set hiring theses for each role with recruiters and hiring managers.
• Oversee evidence-based sourcing across client engagements.
• Own AI-native sourcing workflow and improve search strings and scoring.
• Maintain quality: proof-of-work scoring, no-duplicate rules, and source discipline.
• Hire, train, and QA a bench of contract sourcers.
• Own sourcing scoreboard metrics and report weekly.
• Source senior roles across engineering, AI/ML, and GTM.

Skills

Sourcing

Team leadership

Evidence-based sourcing

AI tooling fluency

Tools

Claude

Exa

Ashby

AI sourcing tools

Job description

Austin, Texas, United States

About the job

Calibratr is an AI-native embedded recruiting firm. We embed full recruiting pods inside fast-scaling seed to Series B AI startups, with a focus on AI in healthcare, and run hiring end to end: sourcing, screening, calibration, and close. We hire on proof of work, not resumes, and calibrate to a founder’s real bar instead of a keyword list.

Our stack pairs experienced recruiters with an AI-native sourcing and evaluation workflow, so a small team moves at the speed our clients need.

Own and scale Calibratr’s sourcing function across every client engagement. This is a player-coach role: you run high-bar searches yourself and build the team, tooling, and quality bar that let a small pod out-source firms ten times our size.

What you’ll own

• Set the hiring thesis for each role alongside the recruiter and hiring manager: the actual problem the role solves and where that person works today, not a mirror of the job description.
• Run and oversee evidence-based sourcing across our client book, building shortlists against tight specs (stage, stack, geo) with candidate rationale a founder can act on.
• Own our AI-native sourcing workflow (Claude, Exa, Ashby, AI sourcing tools) and keep improving it: search strings, scoring, dedup, and calibration loops against real client feedback.
• Hold the quality bar: enforce proof-of-work scoring, our client-exclusion and no-duplicate rules, and verbatim-source discipline so nothing goes out half-checked.
• Hire, train, and QA a bench of contract sourcers, calibrate them fast, and keep the bar consistent across everyone.
• Own the sourcing scoreboard: shortlist-to-screen-pass rate, volume, and turnaround per client, and report it weekly.
  
• You’ve personally sourced senior and staff-level roles (engineering, AI/ML, GTM), not just run high-volume pipelines.
• You can read a technical spec and tell the difference between “worked somewhere that uses X” and “built the thing.”
• You’ve managed or trained other sourcers and can hold a calibration bar across a team.
• You’re fluent with AI-native sourcing tools, or you pick up new tools fast and have real opinions about how to use them well.
• You write clearly. Your candidate rationale goes straight to founders.
• You default to high agency: you unblock yourself, flag a bad spec early, and don’t wait to be told.
  

Bonus

• You’ve sourced in AI or healthcare talent markets (HIPAA/FHIR, clinical, applied AI and agents, MLE).
• You’ve built or heavily used LLM workflows for sourcing or candidate evaluation.
  

How we work:

Remote-first, US hours. Small team, direct access to founders, fast feedback.