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This listing doesn't post a salary. Most similar roles pay
$174,587–$254,750.
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 Staff AI Platform Engineer joins the BTS Business Technology Services team to drive architecture and delivery for Abbott's enterprise AI Platform. This senior individual-contributor role involves leading the design of major platform capabilities, including multi-provider model gateways, GenAI runtimes, agent registries, and evaluation pipelines. You will make critical architecture decisions regarding the control plane, paved-road SDKs, and developer experience while managing platform observability, security guardrails, and responsible-AI controls for PII/PHI handling. The role requires expertise in Python and at least one of TypeScript, Go, or Java, alongside experience with Kubernetes, distributed systems, and API design. You will solve complex technical problems involving RAG, model routing, and platform governance within a highly regulated health tech environment, ensuring scalable, secure, and cost-effective production infrastructure.
Lead the design of major platform capabilities like multi-provider model gateways and GenAI runtimes.
Document architecture decisions and tradeoffs for the platform's control plane, SDKs, and developer experience.
Drive platform observability and evaluation strategies including distributed tracing and quality signals.
Implement security guardrails and responsible-AI controls for PII/PHI handling and prompt-injection defenses.
Own platform reliability by defining SLOs, leading incident response, and driving root-cause analysis.
Set engineering standards through architecture reviews, design documents, and code reviews.
Provide build-versus-buy and vendor recommendations with detailed cost and tradeoff analyses.
Mentor mid-level and junior engineers and act as a technical lead on cross-team initiatives.
What we're looking for
8–10 years of software engineering, platform engineering, distributed systems, or infrastructure experience.
Hands-on experience designing and operating enterprise AI/GenAI platforms or comparable developer, data, or ML platforms in production at scale.
Strong software engineering ability in Python and at least one of TypeScript, Go, or Java, including distributed systems, API design, testing, and secure SDLC.
Deep technical understanding of at least two of: model gateways, GenAI runtimes, RAG, agent/model registries, evaluation, observability/tracing, guardrails, or platform governance.
Experience with containers and orchestration (e.g., Kubernetes), infrastructure as code, CI/CD, cloud services, and production SLO/on-call practices.
Bachelor's degree in a related field or equivalent professional experience.
Demonstrated ability to drive technical decisions with significant autonomy and communicate clearly with technical leadership.
Experience in a highly regulated environment such as health tech, med-tech, or life sciences (preferred).
LLM
AI Engineering
Distributed Systems
Platform Engineering
Kubernetes
Infrastructure as Code
Observability
Retrieval
Tool Calling
Model Routing
Guardrails
Production Systems
Python
Azure ML SDK
Databricks
MLflow
Kubeflow
Docker
Kubernetes
CI/CD
Infrastructure as Code
Data Lake
Feature Store
LLM
Model Monitoring
ETL
Time-series Data
IoT
Mobile