Principal AI/ML Engineer for Health Tech & LLM Platforms

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 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.