Head of AI and Data Platform

Abbott

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Alameda, CA
Salary
$172,000–$344,000 / yr
Employment
Full-time
Posted
62 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $220k
This role $258k
$145k $365k
below market most similar roles pay here above market

This role pays more than 73% of similar roles. Most pay $179,850–$260,262 — the blue band above. At the midpoint, this role pays about $258k versus about $220k for comparable roles.

Based on 240 similar postings.

Employer

About Abbott

Abbott Laboratories is a global healthcare company that manufactures and markets a broad and diversified line of health care products including diagnostics, medical devices, nutritionals, and branded generic pharmaceuticals. Industry: Healthcare & Medical Devices

Abbott currently has 193 open roles on FindRole.

Listed pay typically runs $99,300–$198,700 across 123 roles with salary data.

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At a glance

TL;DR · Head of AI and Data Platform

The Head of AI and Data Platform leads the engineering execution for Lingo, a biosensing technology platform that tracks biomarkers like glucose and lactate. This leadership role requires a hands-on builder to define the technical architecture for AI, machine learning, and data infrastructure. You will design and own data ingestion pipelines, feature stores, model serving layers, and data lake designs while building AI-powered features like personalized metabolic insights and LLM-based conversational health experiences. Key responsibilities include establishing MLOps infrastructure, RAG pipeline architectures, and prompt engineering practices. You must utilize cloud platforms like Azure, AWS, or GCP to manage real-time biosensor data. The role solves the technical challenge of delivering scalable, production-ready AI systems within a regulated health context involving HIPAA, GDPR, and FDA software guidance.

What you'll do

  • Define and own the technical architecture for AI and data platform infrastructure, including ingestion pipelines and data lakes.
  • Drive the engineering execution of AI-powered product features like personalized health insights and LLM-based conversational experiences.
  • Establish engineering standards for model integration, RAG pipelines, prompt engineering, and responsible AI guardrails.
  • Lead the development, training, and deployment of ML models to ensure production reliability and observability.
  • Build and manage MLOps infrastructure for experiment tracking, automated retraining, and model monitoring.
  • Partner with Data Science and Product teams to translate research into scalable, production-ready AI systems.
  • Ensure all AI and ML systems comply with HIPAA, GDPR, and FDA software guidance.
  • Define and report on engineering OKRs, KPIs, and delivery metrics to senior stakeholders.

What we're looking for

  • 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.
  • Proven hands-on experience architecting and building large-scale data platforms on cloud platforms like Azure, AWS, or GCP.
  • Deep system design expertise in distributed data systems and real-time biosensor data pipelines.
  • Meaningful hands-on experience engineering AI-powered products, including LLM integration and RAG pipelines.
  • Strong understanding of AI/ML system design, including model serving, observability, and safety constraints in health domains.
  • Exceptional executive communication skills to translate AI complexity into business narratives for C-suite and board audiences.

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