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Bestow is a vertical technology platform serving major life insurers, unifying legacy value chains and enabling carriers to launch products in weeks instead of years. The Quality Engineering organization is building the verification backbone for an AI-enabled software development lifecycle, emphasizing specification-driven development, requirements-to-test traceability, and non-functional verification.
This Staff Quality Engineer role is embedded within Bestow's Innovation Lab (R&D group) and scales quality practices across Engineering. You will work alongside domain experts, researchers, product engineering teams, Platform Engineers, Technical Program Managers, Compliance, and the broader Quality Engineering team, reporting to the Director of Quality.
The role emphasizes exploratory testing and risk-informed quality assurance rather than downstream test automation alone. Key responsibilities include:
**Testing & R&D Embedding (~40%):** Embed with Labs/R&D through invention and specification phases, developing product models early, capturing risks and questions before they become code. Design and execute chartered, time-boxed testing sessions with structured debriefs to validate testing ROI. Investigate critical failure modes that automated checks cannot catch: multi-tenant isolation, configuration interactions, concurrency, lifecycle state transitions, integration timing, operability gaps, and long-horizon temporal behavior (renewals, lapses, endorsements).
**Risk Modeling & Analysis:** Use the Heuristic Test Strategy Model to identify and document risks across product elements (structure, function, data, interfaces, platform, operations, time). Maintain a living risk catalogue across policy lifecycle, claims, partner integrations, and regulatory workflows. Express each significant risk as a failure story: what could go wrong, who it would harm, and why it is plausible.
**Findings & Reporting:** Report findings in four distinct categories—bugs (product threats), risks (plausible failure stories), questions about intent (specification gaps), and obstacles to testing (testability limits, missing observability). Each category requires different organizational responses.
**Coverage & Testability:** Maintain coverage and testability maps documenting what has been examined, what remains, and structural gaps in the product's observability and testability.
The organization distinguishes testing from checking: checks apply decision rules to observations; testing is the process of learning about a product through exploration, experimentation, questioning, and inference. Tools (including AI) extend the tester's capabilities for data generation, state manipulation, differential comparison, and log analysis. Testers inform decisions; they do not own quality. The north star is giving stakeholders accountable for a release the clearest possible account of the product and its risks, including honest accounting of what was not examined.
