About the role:
- Most teams trade speed for quality. We believe quality is what enables speed.
- We are building an AI-first engineering organization where teams ship fast, confidently, and continuously. That only works when quality, data, and delivery are designed as a system—not separate functions.
- This is not a traditional QA role. It is not project management. This is a high-ownership position where you define how an AI-first team builds, validates, and ships production software.
Key Responsibilities:
- Build Quality as a System
- Turn quality into developer behavior, not a downstream gate
- Design automated testing systems that act as guardrails
- Define and enforce what “production-ready” means through systems
- Enable teams to anticipate edge cases, failures, and data issues early
- Eliminate “hope-driven” releases
- Define What’s Buildable
- Partner with Product and Sales to validate ideas early
- Assess feasibility, data requirements, trade-offs, and cost
- Translate ambiguity into clear, executable plans
- Shape viable ideas and stop unworkable ones early
- Own the Data Reality
- Map how data actually flows across systems and integrations
- Identify gaps, inconsistencies, and reliability issues
- Ensure features are grounded in real, usable data
- Navigate internal and third-party data ecosystems confidently
- Bring Domain Expertise
- Apply knowledge of MarTech / AdTech (identity, activation, measurement)
- Operate within healthcare data constraints and compliance requirements
- Ensure solutions are technically sound and market-relevant
- Drive Delivery End-to-End
- Own delivery for AI-first engineering teams
- Break down work into transparent, actionable steps
- Maintain predictable delivery without slowing velocity
- Proactively identify risks and adjust early
- Align Product, Engineering, and GTM teams.
- Redefine QA for AI Systems
- Develop testing strategies for AI-generated, non-deterministic syste