Director, Test Engineering

Abbott•Alameda, CA

1d•Onsite

About The Position

At Lingo, we’re building a groundbreaking health platform that combines continuous biosensor data, real-time analytics, and personalized insights to help people live fuller, longer, and healthier lives. Our systems ingest millions of sensor readings daily, powering experiences for consumers and partners worldwide, with the reliability and scalability of cloud-native, enterprise-grade platforms. We are looking for a Director of Test Engineering to help accelerate growth across the U.S., Spain, and India. In this role, you will build and lead a world-class, globally distributed software test engineering function. The role requires a hands-on leader who thrives in building, can roll up their sleeves alongside their team, and understands that quality in a consumer health platform is both a technical discipline and a direct expression of how much we care about the people using our product. You will own the end-to-end software testing strategy across Lingo’s platforms, mobile applications, CGM and biosensor data pipelines, AI/ML models, and the broader consumer platform. You will also grow and unify a global team of software quality engineers who operate with the same standards and urgency regardless of time zone.

Requirements

Bachelor’s degree in software engineering or a related field, or equivalent practical experience.
15+ years in software or test engineering, including 5+ years leading and scaling engineering managers and global quality teams.
Demonstrated experience building quality engineering functions—not just running them—including hiring, org design, tooling strategy, and culture development across distributed teams.
Hands-on background in mobile quality engineering (iOS and/or Android), with experience testing consumer-facing applications at scale.
Experience with quality strategy for data-intensive platforms, including IoT, sensor data pipelines, or real-time data processing systems.
Proficient with modern automation frameworks across mobile (Appium, XCTest, Espresso), API (REST Assured, Postman, Pact), and pipeline testing.
Strong knowledge of CI/CD systems and experience integrating automated quality signals into engineering delivery workflows.
Experience owning quality compliance in a regulated environment, with working knowledge of IEC 62304, ISO 13485, 21 CFR Part 820, and related standards.
Strong executive communication skills, with the ability to represent quality engineering to senior leadership and external stakeholders across cultures and time zones.
Proven ability to lead through influence in a fast-paced, cross-functional consumer technology environment.

Nice To Haves

Experience scaling engineering teams across US, European, and Asian geographies, with sensitivity to cross-cultural leadership and distributed team dynamics.
Background in AI/ML system testing, including model validation, drift detection, and testing for probabilistic outputs in consumer health contexts.
Experience with CGM, bio-wearable, or medical device software quality, particularly where hardware and software quality intersect.
Previous experience supporting Regulatory Affairs/Quality Assurance teams during FDA or CE mark audits in a consumer health or digital health context.
Background in non-functional and performance testing tools (e.g., Locust, JMeter, Gatling, k6) applied to high-throughput consumer data platforms.

Responsibilities

Architect and scale a distributed software test engineering team across the U.S., Spain, and India, establishing the hiring strategy, team structure, and operating model that supports Lingo’s growth trajectory.
Create a unified quality engineering culture across geographies, operating with the same standards, tools, and sense of ownership.
Define career paths, mentorship frameworks, and performance expectations that attract and retain top quality engineering talent globally.
Oversee test function staffing, resource planning, budgeting, tooling, test platforms, and third-party vendor relationships across all regions.
Own the quality architecture and test strategy across Lingo’s full technology stack, iOS and Android consumer applications, CGM and biosensor data ingestion pipelines, AI/ML inference services, and backend platform services.
Lead verification strategy for biosensor and CGM data integrity, ensuring that data flowing from wearable hardware through ingestion pipelines to consumer-facing insights is accurate, reliable, and auditable.
Build and maintain the testing infrastructure required to support continuous, high-frequency releases across mobile and platform surfaces.
Establish standards for CI/CD integration of automated test suites, ensuring quality signals are fast, reliable, and actionable for engineering teams.
Champion a shift-left testing culture, embedding quality thinking into design and development rather than treating it as a gate at the end of the cycle.
Serve as the primary engineering owner for test-related compliance activities, including audit readiness, CAPA responses, and regulatory evidence across applicable standards (IEC 62304, ISO 13485, 21 CFR Part 820, 21 CFR Part 11).
Partner with Regulatory Affairs and Legal to ensure test engineering practices remain aligned with applicable FDA, HIPAA, and GDPR requirements as Lingo scales internationally.
Translate regulatory requirements into practical engineering standards that the global team can implement consistently, without creating unnecessary friction in the development process.
Serve as the voice of software quality in product and engineering leadership discussions, surfacing risks, influencing roadmap prioritization, and ensuring that consumer experience software quality is a first-class consideration alongside feature velocity.
Collaborate with Product, Data Science, and Platform Engineering leaders to define shared quality standards across Lingo’s technology organization.
Build post-deployment monitoring and observability capabilities that give the team real-time visibility into quality signals in production, particularly for biosensor data accuracy and AI/ML model performance.