Head of Product Engineering

Abbott•Alameda, CA

1d•$172,000 - $344,000•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 seeking an experienced and strategic Head of Product Engineering who can set the technical direction and roll up their sleeves to solve hard engineering problems. This is a hands-on leadership role for a builder, someone who has personally architected and delivered large-scale SaaS systems, brings deep system design instincts, has meaningful experience engineering AI-powered products, and knows how to grow and galvanize engineering teams to ship great products in a regulated, fast-moving environment.

Requirements

Bachelor’s degree in engineering, computer science, or a related field, or equivalent practical experience.
18+ years of progressive experience in software engineering, with a strong foundation as an individual contributor before moving into leadership, you have written production code and designed systems at scale
Proven hands-on experience architecting and building large-scale SaaS platforms, including multi-tenant architectures, event-driven systems, RESTful and GraphQL APIs, and cloud-native infrastructure (AWS, GCP, or Azure)
Deep system design expertise, you can whiteboard and lead design of distributed systems, data models, caching strategies, and real-time data pipelines from first principles
Meaningful hands-on experience engineering AI-powered products including integrating LLMs into production systems, building RAG or agentic pipelines, and applying ML models within user-facing applications
Strong understanding of AI/ML system design considerations: model serving infrastructure, latency and cost trade-offs, evaluation and observability, data feedback loops, and safety constraints in sensitive domains
Demonstrated success building and scaling high-performing product engineering organizations, with direct ownership of consumer-facing products at significant scale
Deep expertise in engineering organizational design, squad/tribe models, and building high-output teams across web, mobile, backend, and AI/ML disciplines
Proven ability to drive multi-year product engineering roadmaps in regulated, fast-paced environments with demanding reliability and safety requirements
Exceptional executive communication skills, including the ability to translate engineering and AI complexity into clear product and business narratives for C-suite and board audiences
A track record of building and maturing engineering governance frameworks, delivery planning processes, and performance management systems across product engineering organizations

Nice To Haves

Background in digital health, consumer health technology, or other highly regulated industries (e.g., HIPAA, GDPR, FDA oversight)
Experience applying AI/ML in health or wellness contexts, including personalization engines, anomaly detection on sensor data, or clinically informed recommendation systems
Experience in high-growth scale-up or venture-backed environments, with exposure to rapid product and organizational scaling
Hands-on experience with IoT or biosensor data ingestion pipelines, real-time analytics, or wearable device platforms
Experience with IEC 62304–based software development processes for medical device software
Strong experience defining OKRs, KPIs, and capacity planning for high-throughput, consumer-facing platforms with high-availability requirements

Responsibilities

Serve as the principal engineering leader and hands-on architect for product-facing teams, translating product roadmaps and business objectives into a prioritized, executable engineering strategy
Actively participate in system design reviews, architecture decisions, and critical technical problem-solving not just as a reviewer, but as a contributor
Define and own the SaaS architecture strategy for Lingo's consumer platform, including multi-tenancy models, API design, service decomposition, data pipelines, and platform scalability
Drive the architecture and engineering execution of AI-powered product features, including personalized health insights, predictive analytics, LLM-based conversational experiences, and on-device ML inference from biosensor data
Establish engineering standards for AI system design, including model integration patterns, RAG pipelines, prompt engineering practices, evaluation frameworks, and responsible AI guardrails appropriate for a regulated health context
Build, lead, and scale a Product Engineering organization, including Frontend Engineers, Backend Engineers, Mobile Engineers, Full-Stack Engineers, and AI/ML Engineers across multiple product squads
Lead engineering effectiveness initiatives across the Product Engineering function, including team topology design, capability assessments, and engineering culture health
Identify technical debt, architectural risks, and organizational blockers to product delivery velocity and drive sustainable interventions to resolve them
Own and continually improve engineering hiring, onboarding, and career development processes for the Product Engineering organization
Champion engineering best practices like test-driven development, continuous delivery, API-first design, and design-for-reliability to optimize end-to-end product value streams
Standardize tools, development processes, and engineering practices across product squads to improve alignment and delivery consistency
Partner with Product Management, Data Science, and Design on roadmap prioritization, resource allocation, and capacity forecasting across product initiatives
Define, manage, and report on engineering OKRs, KPIs, and delivery metrics; present progress and insights to senior stakeholders
Ensure product engineering investments and AI systems maintain ongoing alignment with regulatory requirements, including HIPAA, GDPR, and FDA software guidance, in close partnership with Legal and Compliance
Own release cadence, feature delivery readiness, and global deployment coordination with Platform Engineering and Product teams