Principal Engineer, AI Platform, AI Factory / Advance AI

Target

Remote Hybrid

Quick summary

Work type: Remote
Location: Remote
Salary: $168,000–$303,000 / yr
Posted: 6 days ago
Closes: Jul 31, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $209k

This role $236k

$152k most similar roles pay here $319k

This role pays more than 64% of similar roles. Most pay $171,875–$246,150 — the shaded band above. At the midpoint, this role pays about $236k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About Target

Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail

Target currently has 56 open roles on FindRole.

Listed pay typically runs $106,500–$208,500 across 56 roles with salary data.

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View all roles at Target

At a glance

TL;DR · Principal Engineer, AI Platform, AI Factory / Advance AI

Role Posting Log in to save

As a Principal Engineer in Target's AI Platform organization, you will lead the technical direction for the enterprise ML Operations Platform, defining long-term architecture and standards for machine learning lifecycle management. Your responsibilities include designing scalable cloud-native platforms, establishing best practices for model development and deployment, and partnering with cross-functional teams to enhance platform scalability and operational efficiency. You will mentor senior engineers, evaluate emerging technologies, and guide strategic investments that improve developer productivity and accelerate AI adoption. The role requires extensive experience in large-scale cloud-native systems, enterprise machine learning platforms, and MLOps capabilities, as well as expertise in Kubernetes-based platforms, CI/CD practices, and modern platform engineering techniques.

Skills

Vertex AI Kubeflow MLflow Terraform GitOps Kubernetes CI/CD Infrastructure as Code Prometheus Grafana Docker Python PostgreSQL AWS Azure Generative AI Feature management Model governance Responsible AI

What you'll do

Define long-term architecture for enterprise ML Operations Platform.
Design secure cloud-native platforms for machine learning workloads.
Establish best practices for model lifecycle management.
Lead infrastructure for batch, streaming, and real-time inference systems.
Drive adoption of Kubernetes and modern platform engineering practices.
Define standards for model governance and responsible AI.

What we're looking for

Extensive experience designing and delivering large-scale cloud-native platforms or distributed systems.
Deep experience building and operating enterprise machine learning platforms and MLOps capabilities.
Demonstrated experience with machine learning lifecycle management, deployment strategies, observability, and production operations.
Expertise in Kubernetes-based platforms supporting AI and machine learning workloads.
Experience mentoring senior engineers and leading enterprise-scale modernization initiatives.
Strong understanding of software engineering best practices including CI/CD, infrastructure as code, testing, and automation.

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