JOB DESCRIPTION:Head of AI and Data Platform
Lingo Division - Abbott
Location: Alameda, CAAbout LingoMeet 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 OPPORTUNITYAt 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 perform reliably at consumer scale.
- Define standards for LLM integration, including prompt management, retrieval-augmented generation, evaluation harnesses, latency and cost optimization, and safety guardrails for health-related conversational AI.
- Ensure AI and ML systems maintain ongoing alignment with regulatory requirements including HIPAA, GDPR, and FDA software guidance, in close partnership with Regulatory Affairs, Legal, and Quality Assurance.
- Define, manage, and report on engineering OKRs, KPIs, and delivery metrics for the AI and Data Platform function, presenting progress and insights to senior stakeholders.
- Standardize tools, development processes, and data engineering practices across AI and data squads to improve alignment, data quality, and delivery consistency.
Required Qualifications:- Bachelor's degree in computer science, Engineering, Mathematics, or a related technical discipline. Advanced degree in Machine Learning, Data Science, or equivalent preferred.
- 15+ years of progressive experience in software and data engineering, with a strong foundation as an individual contributor who has personally built production AI and data systems at scale before moving into leadership.
- Proven hands-on experience architecting and building large-scale data platforms, including real-time streaming pipelines, data lakes, feature stores, and ML serving infrastructure on cloud platforms (Azure, AWS, or GCP).
- Deep system design expertise in distributed data systems: you can whiteboard and lead the design of event-driven data architectures, data models, caching strategies, and real-time biosensor 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 deploying ML models within consumer-facing applications.
- Strong understanding of AI and ML system design considerations, including model serving infrastructure, latency and cost trade-offs, evaluation frameworks, observability, data feedback loops, and safety constraints in sensitive health domains.
- Exceptional executive communication skills, including the ability to translate AI and data complexity into clear product and business narratives for C-suite and board audiences.
Preferred Qualifications- Background in digital health, consumer health technology, or other highly regulated industries such as HIPAA, GDPR, and FDA oversight.
- Hands-on experience with IoT or biosensor data ingestion pipelines, real-time analytics, or wearable device platforms.
- Experience applying AI and ML in health or wellness contexts, including personalization engines, anomaly detection on sensor data, or clinically informed recommendation systems.
- Experience with IEC 62304-based software development processes for medical device software.
- Experience in high-growth scale-up or venture-backed environments with exposure to rapid product and organizational scaling.
- Strong experience defining OKRs, KPIs, and capacity planning for high-throughput, consumer-facing AI platforms with high-availability requirements.
Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com
The base pay for this position is $172,000.00 - $344,000.00
In specific locations, the pay range may vary from the range posted.
JOB FAMILY:Product Development
DIVISION:LNGO Lingo
LOCATION:United States > Alameda : 2901 Harbor Bay Parkway
ADDITIONAL LOCATIONS:WORK SHIFT:Standard
TRAVEL:Yes, 15 % of the Time
MEDICAL SURVEILLANCE:Not Applicable
SIGNIFICANT WORK ACTIVITIES:Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
