Vida Health

Product Manager

• Own the configuration platform backlog: prioritize what gets built, define it clearly, ship it and measure.
• Translate operational input from client success, operations and clinical teams into clean, right-sized product work that doesn't slow down implementation or degrade member experience quality.
• Deliver new features across the platform's vertical domains (program setup, eligibility, content configuration, clinical protocol settings, billing rules) based on operational urgency and technical dependencies.
• Own quality, triage bugs, track reliability and hold the bar for internal users who depend on this platform every day to do their jobs.
• Keep engineering moving: unblock delivery, make tradeoffs explicit and close the loop between what's scoped and what ships.
• Use AI tools like Claude Code to prototype platform concepts, scaffold UI and put working software in front of internal users to validate ideas before engineering resources are committed.
• Work with engineering to identify which components are good candidates for AI-assisted development.
• Compress the concept-to-feedback cycle.
• Define what good looks like for this platform: time-to-configure, error rates, support ticket volume and internal user adoption. Then build the dashboards and own the measurement.
• Dig into internal user behavior- where are the workarounds, the drop-offs, the broken workflows and support requests?
• Use data to make the case for what gets prioritized next.
• Spend real time with ops and client success teams to understand the workflows you're replacing.
• Coordinate with the member experience PM team so configuration changes don't create surprises on the member-facing side.
• Partner with clinical teams on protocol configuration- safety and quality are non negotiable.
• Make build-vs-configure decisions with engineering and push the architecture toward future vertical expansion.

Product Manager – Client Experience

Accountant

• Perform monthly billing operations including claims reconciliation, account reconciliation and revenue review and validation.
• Contribute to the revenue cycle process, including claims submission, QA, payment posting and AR follow-up.
• Serve as a point of contact for clients; participating in onboarding calls, monthly check-ins and responding to billing questions.
• Collaborate with Sales, Product, Data and Client Success teams on RFPs, internal process updates and issue resolution.
• Additional duties as assigned.

Software Engineer

• Define and build Vida's organizational approach to AI-augmented engineering—turning individual tool usage into a shared, scalable capability.
• Build the institutional knowledge systems that make Vida's architecture, domain context and golden path patterns accessible to both engineers and AI tools.
• Establish technical controls and governance for AI tool usage: approved tools, PHI-safe workflows, prompt guardrails and vendor evaluation processes.
• Own CI/CD reliability and velocity—targeting sub-5-minute median CI with automated preview environments, flake reduction and smart test selection.
• Build paved-road developer workflows: one-command local setup, service templates, repo standards and golden path generators.
• Own core GCP platform systems—compute, networking primitives, deployment automation and infrastructure as code.
• Define and track the metrics that show whether enablement is working: PR cycle time, CI duration, change failure rate, time-to-first-PR for new engineers.
• Hire and grow a team of 1–2 engineers as impact proves out.

Director of Engineering, Enablement and AI Tooling

Data Engineer

• Own end-to-end reliability for core data pipelines—from ingestion through billing and reporting outputs.
• Build observability foundations: health dashboards, tiered alerting and on-call signals that are actionable, not noisy.
• Harden data ingestion with typed staging, quarantine patterns, freshness gates and safe backfill and replay capabilities.
• Enforce schema contracts and quality validation so failures are caught in CI, not discovered by stakeholders.
• Establish clear boundaries between governed core data and downstream BI and reporting layers.
• Lead incident retrospectives that fix root causes, not just symptoms, and reduce future on-call burden.
• Mentor 2–4 data engineers through code reviews, pairing and growth conversations.

Lead Data Engineer, Data Platform

• Own the member experience product backlog: prioritize, scope, ship and measure improvements to the core product (home screen, logging, goal setting, content, care team interactions).
• Drive A/B testing and rapid experimentation to improve engagement, activation and retention metrics.
• Manage bug triage and quality for the member experience; ensure a reliable, performant product.
• Partner with engineering to maintain product velocity, unblock delivery and manage technical tradeoffs.
• Translate client requests and stakeholder input into well-scoped product work without compromising member experience quality.
• Own member experience metrics: engagement (MAU, WAU, DAU), retention, churn, activation rate, NPS and clinical outcomes (5%+ weight loss).
• Build and maintain dashboards in Looker and PostHog; establish regular data review cadence.
• Analyze user behavior to identify friction points, drop-off patterns and opportunities for improvement.
• Design and interpret experiments; bring data-informed recommendations to product and leadership forums.
• Work closely with design to iterate on UX improvements and ensure member-first thinking in all product decisions.
• Partner with clinical teams to ensure product changes support care delivery, medication management and coaching workflows.
• Collaborate with the onboarding PM to ensure seamless handoff from enrollment into the core experience.
• Coordinate with product marketing to improve re-engagement and lifecycle messaging.
• Contribute to the Vida 2.0 vision by surfacing insights from current product performance, member feedback and competitive analysis.
• Help stand up user research infrastructure; recruit participants, support moderated testing and synthesize findings.
• Support concept validation and prototype testing for next-generation member experiences.

Product Manager – Client Experience

Accountant

Director of Engineering, Enablement and AI Tooling

Lead Data Engineer, Data Platform

Senior Product Manager – Member Experience