Provider Operations Lead

Own the end-to-end provider lifecycle—sourcing, onboarding, credential checks, activation, and ongoing quality. You'll build AI-assisted playbooks that lift responsiveness, accuracy, and trust while protecting privacy and regulatory boundaries.

Hybrid (Austin, TX) or Remote (US)

Full-time

Competitive salary + equity

AI-first Provider Quality Compliance AI Ops Operations Leadership Remote

Quality & trust Set the bar for profile accuracy, responsiveness, verified reviews, and safety flags; drive continuous QA sampling.

Compliance Operationalize HIPAA boundaries, CPOM sensitivities, identity & credential checks, and incident playbooks.

AI-assisted ops Deploy AI for triage, classification, de-duplication, and proactive nudges—measured with offline evals and human review.

Leadership Coach a small team; partner with Product, Eng, Data, and Legal; write crisp SOPs and postmortems.

What you'll lead

Onboarding: Credential packet completeness, identity verification, and profile readiness SLAs.

Responsiveness: SLAs and nudges that raise first-response and win-rate versus inquiries.

Issue management: Escalation taxonomy, root-cause analysis, corrective action plans.

AI ops: Prompt/eval sets for classification, routing, de-dup; periodic audits of model drift.

AI-ops framework

What it includes

Examples

Triage & routing LLM-assisted intent detection, specialty tagging, geo validation. Auto-route orthodontics to verified providers within 25mi; flag out-of-scope requests.

Quality automation Profile diffing, duplicate detection, content policy checks. Detect stock images or unverifiable claims; request evidence via templated flows.

Safety guardrails Prompt injection resistance, PHI redaction, allow-listed endpoints. Block free-text storing PHI; escalated edge cases to human review.

Measurement Offline eval sets, cost/latency dashboards, periodic red-team. Monthly audit pass-rate ≥ 97%; rollback criteria defined.

Responsible AI

Use retrieval of vetted content and human-in-the-loop for sensitive actions. Never provide medical advice.

Playbooks & compliance

Operational playbooks

• Quality sampling cadence (AQL), audit trail, corrective actions.
• Escalation matrix for safety/complaints; communication templates.

Compliance & risk

• HIPAA boundary (no PHI to non-approved endpoints) and CPOM awareness.
• BAA/vendor checks for any third-party handling provider or patient data.
• Records retention & privacy notices aligned with jurisdictional rules.

Success metrics

Metric

Definition

Guardrails

Activation rate % of onboarded providers who reach "bookable" within 14 days. No drop in data accuracy or policy adherence.

First response SLA % inquiries answered within target window by specialty. Maintain satisfaction; no templated spam responses.

Profile quality score Weighted completeness + evidence + recency + review integrity. Audit false-positive rate stays ≤ 3%.

Issue resolution time Average time from ticket creation to verified resolution. Recurrence rate declines; root-cause tracked.

AI-ops audit pass rate % sampled AI decisions matching gold labels. No PHI egress; latency/cost within SLOs.

Requirements

Must-have

Nice-to-have

• 5+ years in provider/vendor operations, marketplace ops, or network management.
• Hands-on with SOPs, SLAs, QA sampling, and incident/escalation management.
• Working knowledge of US healthcare basics (HIPAA boundary, credentialing, CPOM sensitivity).
• Data/ops literacy: funnels, cohorts, basic SQL or spreadsheets; comfort with dashboards.
• Clear written communication; experience coaching small ops teams.
• Experience with AI-assisted operations (classification, routing, QA) and evaluation basics.
• Healthcare marketplace or multi-sided platform background.
• Familiarity with Zendesk/Intercom/CRM, workflow tools, or light scripting/automation.

Hiring process

Step

What to expect

Typical time

2) Screen 30 min on ops judgment, SLAs, and AI-ops exposure. ~1 week

3) Deep dive Case walk-through on provider lifecycle and quality; writing sample (SOP/executive brief). ~1 week

4) Practical Time-boxed take-home or prior work review incl. a light AI routing/QA eval task. 3–7 days

5) Panel Cross-functional interviews with Product/Eng/Legal; safety & compliance scenarios. ~1 week

6) Offer Comp band, benefits, start date. Background check post-offer where lawful. 48–72 hours

Equal Opportunity: We welcome applicants of all backgrounds and do not discriminate on any protected basis.

Right to work: US work authorization required for this role; export-control compliance may apply to some tools.