Senior Engineer, AI Platform

Abbott

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Madison, WI
Salary
$99,300–$198,700 / yr
Employment
Full-time
Posted
7 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $197k
This role $149k
$83k $251k
below market most similar roles pay here above market

This role pays less than 87% of similar roles. Most pay $161,875–$232,112 — the blue band above. At the midpoint, this role pays about $149k versus about $197k 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.

Most-posted roles

View all roles at Abbott

At a glance

TL;DR · Senior Engineer, AI Platform

The Sr. Engineer, AI Platform joins the ONCO Cancer Diagnostics division to drive the strategic vision and technical execution for the Cancer Diagnostics AI/ML platform. This hands-on engineering leader is responsible for the architecture, reliability, scalability, and security of the infrastructure layers supporting large language models, predictive models, and agentic systems. Key responsibilities include designing the Kubernetes foundation, managing infrastructure-as-code and GitOps, and operating production model serving and GPU infrastructure. The role involves building workflow orchestration, event-streaming systems, and observability stacks while ensuring compliance with HIPAA, FDA, and GxP frameworks. Required skills include Python, machine learning frameworks, and cloud platforms, with preferred experience in Go, Rust, Knative, KEDA, and service mesh patterns to manage complex multi-tenant isolation and low-latency inference optimization.

What does a Engineer earn?

Median $178175 from 251 postings across 54 companies.

See salary data

What you'll do

  • Design and manage the cloud and Kubernetes foundation, including network topology, VPC design, and production cluster security.
  • Lead platform expansion across multiple regions, managing identity federation, traffic management, and multi-cloud evaluations.
  • Own infrastructure-as-code and GitOps workflows to manage environment promotion, drift control, and CI/CD deployment tooling.
  • Architect and operate production model serving and GPU infrastructure, including inference optimization, autoscaling, and cost attribution.
  • Build and maintain workflow orchestration and event-streaming systems with focus on state-machine design and cross-region replication.
  • Manage the observability stack, disaster-recovery strategies, and lead post-incident analysis for complex infrastructure issues.
  • Implement infrastructure security and governance through least-privilege identity, secrets management, and automated compliance checks.
  • Develop and deploy production software as a hands-on contributor while mentoring engineers and leading long-term technology planning.

What we're looking for

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Demonstrated expertise in designing and deploying cutting-edge AI solutions that drive measurable business impact.
  • Demonstrated understanding of ethical considerations in AI systems.
  • 3+ years of project leadership experience including Agile project management and Scaled Agile Frameworks (SAFE).
  • Advanced ability working with machine learning frameworks, programming languages like Python, and cloud platforms.
  • Strong analytical and problem-solving skills with expertise in AI/ML techniques.
  • Production experience with Python, Go and/or Rust (preferred).
  • Experience leading platform transformations, building large-scale AI infrastructure, or multi-cloud migrations (preferred).

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