Head of AI and Data Platform

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

Head of AI and Data Platform

Lingo Division – Abbott
Location: Alameda, CA

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:

• Career development with an international company where you can grow the career you dream of.
• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution.
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

About Lingo

Meet Lingo, a new biosensing technology that provides users a window into their body. Lingo tracks key biomarkers such as glucose, ketones, and lactate to help people make better decisions about their health and nutrition. Biowearable technology will digitize, decentralize and democratize healthcare, enabling consumers to take control of their own health.

THE OPPORTUNITY

At Lingo, we are 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 AI-driven experiences for consumers and partners worldwide, with the reliability and scalability of cloud-native, enterprise-grade platforms.

We are seeking an experienced and hands-on Head of AI and Data Platform to define the technical vision and lead the engineering execution of Lingo's AI, machine learning, and data infrastructure. This is a leadership role for a builder who has personally architected and delivered production AI and data systems at scale, brings deep technical instincts across ML engineering, data platform design, and LLM-based product development, and knows how to grow and galvanize engineering teams to ship innovative AI-powered health products in a regulated, fast-moving environment.

This is not a strategy-only role. You will be deeply involved in system design, architecture decisions, and critical technical problem solving as a contributor, not just a reviewer, while also building and leading a high-performing global team of AI and data engineers.

What You'll Work On

• Define and own the technical architecture for Lingo's AI and data platform, including biosensor data ingestion pipelines, real-time and batch processing infrastructure, feature stores, model serving layers, and data lake design.
• Drive the architecture and engineering execution of AI-powered product features, including personalized metabolic health insights, predictive analytics from CGM data, LLM-based conversational health experiences, and on-device ML inference from biosensor data.
• Establish engineering standards for AI system design, including model integration patterns, RAG pipeline architecture, prompt engineering practices, evaluation and observability frameworks, and responsible AI guardrails appropriate for a regulated health context.
• Lead the engineering execution of ML model development, training, evaluation, and deployment pipelines, ensuring models reach production reliably, safely, and with the observability required to detect drift and degradation.
• Build and own MLOps infrastructure including experiment tracking, model registry, automated retraining pipelines, A/B testing frameworks, and model monitoring for production AI systems.
• Partner with Data Science and Product teams to translate model research and product requirements into scalable, production-ready AI systems that per