below marketmost similar roles pay hereabove market
This role pays more than
70%
of similar roles. Most pay
$169,550–$239,650
— the blue band above.
At the midpoint, this role pays about
$224k
versus about
$205k
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.
The Principal AI Platform Engineer joins the BTS Business Technology Services team to lead the architecture, engineering, and reliability of the enterprise AI Platform. This player-coach role involves defining reference architectures for the AI control plane, building model gateways for multi-provider routing, and delivering GenAI runtimes for retrieval-augmented generation and vector search. You will manage model, agent, and prompt registries while implementing security guardrails for PII/PHI handling. Key technologies include Python, TypeScript, Go, or Java, alongside Kubernetes, infrastructure as code, CI/CD, and OpenTelemetry. You will solve complex problems regarding tenant isolation, cost allocation, and distributed tracing in a highly regulated health tech environment. Responsibilities include writing production code, conducting architecture reviews, and leading a team of engineers to ensure platform observability and reliability.
Define and evolve the reference architecture for the AI control plane, SDKs, and developer experience.
Design and build a model gateway supporting multi-provider routing, tenant isolation, and cost allocation.
Deliver a GenAI runtime for model serving, RAG, vector search, and sandboxed tool execution.
Own the technical design of model, agent, prompt, and tool registries including versioning and auditability.
Build platform observability and traceability for prompts and agent steps using distributed tracing.
Implement security guardrails, PII/PHI handling, and responsible-AI controls within the platform.
Establish platform engineering practices using Kubernetes, infrastructure as code, and CI/CD to manage reliability.
Hire, coach, and lead a team of 3–8 engineers while remaining hands-on with production code.
What we're looking for
10–15+ years of software engineering, platform engineering, distributed systems, or infrastructure experience, including significant technical leadership.
Hands-on experience designing and operating enterprise AI/GenAI platforms or comparable developer, data, or ML platforms in production.
Strong software engineering ability in Python and at least one of TypeScript, Go, or Java.
Deep technical understanding of model gateways, GenAI runtimes, RAG, agent registries, evaluation, observability, traceability, guardrails, identity, and platform governance.
Experience with containers and orchestration (e.g., Kubernetes), infrastructure as code, CI/CD, cloud services, secrets management, and production SLOs.
Bachelor's degree in a related field or equivalent professional experience.
Demonstrated ability to lead technical decisions, influence across teams, communicate with senior stakeholders, and manage a growing engineering team.
Experience in a highly regulated environment such as health tech, med-tech, or life sciences (preferred).
Remote (Palo Alto, CA)+125 days ago
$242,634–$499,541
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