QA Lead

Blooming Health

15h•Remote

About The Position

As we scale, we’re looking for an ambitious and highly technical QA Lead to build and elevate Blooming Health’s quality engineering function through our next phase of growth. This is a US-based remote role with required overlap on EST hours. This QA Lead will serve as both a hands-on technical quality leader and people manager, partnering closely with Engineering, Product, and AI teams to improve product quality, strengthen QA operational maturity, and scale testing practices across a rapidly evolving SaaS platform. This is not a purely managerial role — we are looking for someone who can actively contribute to test strategy, automation, tooling, and quality initiatives while also leading and developing a distributed QA team. The ideal candidate brings strong QA engineering fundamentals, startup execution experience, and the ability to thoughtfully evolve what modern QA should look like in an AI-driven engineering environment.

Requirements

Deep experience in software quality engineering, including test strategy, automation frameworks, debugging, exploratory testing, and modern QA methodologies.
Comfortable actively contributing as an individual contributor while leading a team.
Able to review architecture, understand systems deeply, and collaborate closely with engineers on technical quality initiatives.
Experience managing QA engineers, including performance management, mentorship, resource allocation, prioritization, and workforce planning.
Proven track record delivering results in fast-paced startup or growth-stage SaaS environments where processes are evolving and teams must balance speed with quality.
Ability to leverage modern AI tools and agents to improve QA productivity, including generating test plans, accelerating automation, and enhancing testing workflows.
Strong ability to deeply understand application architecture, APIs, backend systems, and engineering tradeoffs.
Preference for candidates comfortable working in open-source-oriented engineering environments.
Excellent communication and partnership skills with Engineering, Product, and leadership stakeholders.
Familiarity operating in environments involving sensitive or regulated data and secure development practices.

Nice To Haves

Experience within healthcare technology, HIPAA-regulated environments, or other highly regulated industries is strongly preferred.
Familiarity with evolving QA approaches in AI-enabled development environments, including intelligent test generation and automation workflows.
Experience working within highly technical engineering organizations that emphasize deep system understanding, source code review, and open-source tooling ecosystems.
Experience working with distributed engineering and QA teams across multiple locations and time zones.
Comfortable working across modern SaaS architectures, APIs, backend systems, and automated testing frameworks in language-agnostic environments.

Responsibilities

Define and drive the QA roadmap across the organization.
Establish scalable quality processes, testing standards, metrics, and operational practices that improve product reliability, release confidence, and engineering velocity.
Contribute directly to test planning, automation strategy, debugging, exploratory testing, and quality investigations.
Partner with engineers to deeply understand architecture, systems behavior, and product functionality.
Lead, mentor, and manage the QA engineering team, including performance management, workforce planning, prioritization, and resource allocation across multiple initiatives and product areas.
Evaluate and improve existing QA workflows, automation coverage, release processes, defect management, and overall SDLC quality practices.
Introduce measurable improvements to testing efficiency and product quality.
Leverage modern AI tooling and agentic workflows (Claude, Gemini, etc.) to accelerate test generation, planning, automation, and QA productivity.
Help define how AI can responsibly and effectively modernize QA practices.
Build strong working relationships across Engineering, Product, AI, and Customer-facing teams.
Act as a trusted quality partner who helps balance speed, reliability, and user experience.
Establish quality metrics, reporting, and accountability mechanisms.
Help create visibility into product quality trends, release readiness, production risks, and testing effectiveness.
Ensure QA practices appropriately support secure software development and high standards around sensitive and regulated data environments.