Principal AI/ML Engineer

Abbott; Alameda (CA); On-site; USD 131,000 - 261,000; Full time

Benefits offered by this job

Health coverage

Retirement plan with employer con­tri­

Tuition reimbursement

FreeU education benefit

Job summary

Abbott is seeking a Principal AI/ML Engineer in Alameda, CA to define and build the AI layer that turns glucose data into personalized insights. You will set architecture, guardrails, and evaluation standards for agentic and LLM-based features and lead the AI engineering team.

This hands-on, principal-level role requires collaboration with data science, regulatory, product, and mobile teams, plus a track record of leading architecture decisions and responsible AI practices.

Qualifications

• Ph.D. or master’s degree in computer science, machine learning or a related field.
• Minimum of 10+ years of software or ML engineering experience.
• 3+ years building LLM-based or agentic systems in production.
• Deep experience with agent frameworks, tool calling, retrieval-augmented generation, and prompt evaluation.
• Proven track record designing guardrails, safety controls, and evaluation pipelines for user-facing AI.
• Strong proficiency in Python and cloud platforms (Azure, AWS, or GCP).
• Demonstrated technical leadership, setting architecture and standards across teams.
• Ability to operate with little instruction and minimal supervision.
• Excellent written and verbal communication skills, able to explain AI risk and trade-offs to clinical, regulatory, and executive audiences.

Responsibilities

• Define the technical vision and architecture for agentic and LLM-based features across cloud and device.
• Design and build agents that combine glucose history, model predictions, meals, activity, and user context to deliver actionable insights.
• Own agent orchestration, tool use, memory, and retrieval patterns, choosing between hosted and self-managed models based on safety, cost, and latency.
• Stay current on advances in LLMs and agentic systems and translate them into a practical roadmap.
• Establish guardrails so agent responses stay within approved product and regulatory claims.
• Build evaluation frameworks with clinically grounded test sets, co-owned with data science and clinical teams, covering accuracy, safety, and user impact.
• Ensure every agent response is traceable and auditable in line with design controls and regulatory requirements.
• Partner with regulatory and quality teams on risk analysis, documentation, and evidence for AI-enabled features.
• Use sound judgement and discretion when handling confidential and personal health data.
• Provide technical leadership and mentorship across the AI engineering team and lead architecture and design reviews.
• Productionize time-series and personalization models for glucose insights, from prototype to scalable, monitored services.
• Build batch and real-time inference services with defined latency, cost, and availability targets.

Skills

Python programming

LLM/agentic systems

Cloud platforms (Azure/AWS/GCP)

Technical leadership

Excellent communication

Education

Ph.D. or master's in computer science or ML

Job description

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 122,000 colleagues serve people in more than 160 countries.

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.

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 forfree medical coverage in ourHealth Investment Plan (HIP) PPOmedical 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.

THE OPPORTUNITY

Principal AI/ML Engineer

Location: Alameda, CA.

As Principal AI/ML Engineer, you will define and build the AI layer that turns glucose data and model outputs into personalized, conversational insights for users. You will set the architecture, evaluation standards, and guardrail policy for all agentic and LLM-based features, and act as the technical lead for the AI engineering team.

This is a hands-on, principal-level individual contributor role and a founding position on the team, with direct influence on its architecture, standards, and future hires. You will work closely with data science, clinical, regulatory, product, and mobile engineering, so a high level of technical judgement and professionalism is required.

What You’ll Work On

• Define the technical vision and architecture for agentic and LLM-based features across cloud and device.
• Design and build agents that combine glucose history, model predictions, meals, activity, and user context to deliver actionable insights.
• Own agent orchestration, tool use, memory, and retrieval patterns, choosing between hosted and self-managed models based on safety, cost, and latency.
• Stay current on advances in LLMs and agentic systems and translate them into a practical roadmap.
• Establish guardrails so agent responses stay within approved product and regulatory claims, including no unapproved dosing or treatment advice.
• Build evaluation frameworks with clinically grounded test sets, co-owned with data science and clinical teams, covering accuracy, safety, and user impact.
• Ensure every agent response is traceable and auditable in line with design controls and regulatory requirements.
• Partner with regulatory and quality teams on risk analysis, documentation, and evidence for AI-enabled features.
• Use sound judgement and discretion when handling confidential and personal health data.
• Provide technical leadership and mentorship across the AI engineering team and lead architecture and design reviews.
• Productionize time-series and personalization models for glucose insights, from prototype to scalable, monitored services.
• Build batch and real-time inference services with defined latency, cost, and availability targets.

Required Qualifications

• Ph.D. or master’s degree in computer science, Machine Learning or a related field.
• Minimum of 10+ years of software or ML engineering experience, including 3+ years building LLM-based or agentic systems in production.
• Deep experience with agent frameworks, tool calling, retrieval-augmented generation, and prompt and model evaluation.
• Proven track record designing guardrails, safety controls, and evaluation pipelines for user-facing AI.
• Strong proficiency in Python and cloud platforms (Azure, AWS, or GCP).
• Demonstrated technical leadership, setting architecture and standards across teams without direct authority.
• Ability to operate with little instruction and minimal supervision.
• Excellent written and verbal communication skills, able to explain AI risk and trade-offs to clinical, regulatory, and executive audiences.

Preferred Qualifications

• Experience in a regulated industry, ideally medical devices, digital health, or SaMD.
• Experience with physiological or wearable sensor data, such as continuous glucose monitoring.
• Experience with on-device or small language models.
• Publications, patents, or open-source contributions in applied AI.
• Experience with personalization, recommendation, or anomaly detection systems.
• Familiarity with HIPAA and data privacy requirements.
• undefined

Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.

Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter AbbottNews and @AbbottGlobal

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The base pay for this position is $130,700.00 – $261,300.00. In specific locations, the pay range may vary from the range posted.