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← cloverhealth / Senior Product Manager, Customer Integrations

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role
cloverhealth / Senior Product Manager, Customer Integrations
model
anthropic/claude-sonnet-4.6
created
2026-05-27T17:43

Company snapshot

Counterpart Health is a subsidiary of Clover Health focused on AI-enabled primary care tooling; its flagship product, Counterpart Assistant, is used by thousands of practitioners to support chronic condition management within physician workflows. Clover Health is a publicly traded Medicare Advantage insurer (NASDAQ: CLOV) that has leaned heavily into value-based care and proprietary data infrastructure as its competitive differentiator. Counterpart Health was spun out (or operationally separated) to commercialize the clinical AI platform beyond Clover's own membership, targeting payer and provider partners. The company operates remote-first and has been expanding its enterprise customer base, which is the direct driver of this integration PM hire. Engineering reputation is not widely documented publicly; based on the JD, the team appears to value empowered, technically deep PMs who can operate close to data pipelines and enterprise customer relationships.

Team stack

Based on the JD and Clover Health's publicly known infrastructure: healthcare data interchange likely involves HL7 FHIR and/or EDI 837/835 claims formats (likely), with internal data pipelines on cloud infrastructure (AWS or GCP, uncertain). Data storage likely involves columnar or time-series stores for claims and clinical data (likely Snowflake or BigQuery, based on industry norms). Integration tooling likely includes ETL/ELT pipelines (dbt, Airflow, or similar, inferred). Provider-facing product (Counterpart Assistant) is a web application; clinical data types explicitly called out include claims, pharmacy, labs, enrollment, provider alignment, and medical records — suggesting NCPDP, HL7 v2/FHIR, X12 EDI familiarity is expected. AI augmentation of data ops is explicitly required; specific tooling not named in JD.

Likely questions (10)

areaquestionwhy
domain Walk me through how you would onboard a new payer customer's claims and pharmacy data — from contract signature to 'data is fit for purpose' in our clinical workflows. What are the failure modes you'd anticipate? The JD explicitly calls out accountability for the full lifecycle from onboarding through ongoing data health across claims, pharmacy, labs, enrollment, and clinical data.
system_design How would you design a reusable integration playbook and monitoring framework so that each new customer integration is faster than the last? What does the 'compounding infrastructure' look like concretely? The JD states 'every integration you run should make the next one faster' and calls out playbooks, standard data expectations, reusable patterns, and monitoring frameworks as explicit deliverables.
domain Healthcare data sources — claims, labs, enrollment — are notoriously messy. Describe a specific data quality issue you've encountered (or would anticipate) and how you'd triage, escalate, and resolve it before it surfaces in product behavior. The JD calls out 'data issues are identified and resolved before they surface in product behavior or customer feedback' as a success metric, and asks for deep working knowledge of how these sources 'commonly fall short.'
behavioral Tell me about a time you managed multiple concurrent enterprise integration efforts. How did you maintain momentum across a growing portfolio and make prioritization calls when resources were constrained? The JD explicitly requires managing multiple customer integrations in parallel and maintaining momentum across a growing portfolio.
behavioral Describe a situation where you were the primary technical counterpart for an enterprise customer on a data delivery or integration problem. How did you build trust while also holding them accountable to timelines and data quality standards? The JD emphasizes direct enterprise customer relationships, driving execution, resolving quality issues, and 'building the kind of trust that comes from deep technical engagement.'
domain How familiar are you with value-based care data operations — specifically provider alignment, risk adjustment, and how claims completeness affects quality metrics like HEDIS or HCC capture rates? Counterpart Health's core use case is chronic condition management and value-based care; the JD calls out payer, provider, and VBC data operations experience explicitly.
system_design How would you use AI to automate data validation and quality triage in a healthcare integration pipeline? Be specific about where AI adds the most leverage versus where human judgment is still required. The JD calls out 'AI-augmented data operations' as a core responsibility and states the candidate must 'see AI as essential to data operations, not optional.'
coding Given a sample claims file with missing member IDs, duplicate dates of service, and mismatched provider NPIs, how would you write a validation script or spec to catch these issues systematically? What would your data expectation framework look like? The JD requires building 'standard data expectations' and the candidate is expected to work directly with customer data — a light technical screen on data literacy is likely.
behavioral Tell me about a 0-to-1 platform or infrastructure product you built. How did you define 'done,' and how did you balance building for the immediate customer versus building for scale? The JD asks for someone who 'builds infrastructure that scales' and 'thinks in terms of patterns and systems' — Intuit ICE Self-Service and SDK work are directly relevant here.
culture This role sits at the intersection of clinical product, analytics, engineering, and enterprise customers — with significant ambiguity and limited direction. How do you operate in an empowered PM model, and how do you decide when to escalate versus drive forward independently? The JD explicitly states 'you thrive in an empowered product organization and can drive a roadmap with limited direction' — a culture/operating-style signal.

Talking points