Lead AI Engineer — Hybrid for Advanced AI Solutions

Target; Brooklyn Park (MN); Hybrid; USD 132,000 - 286,000; Full time

Benefits offered by this job

Health benefits

401(k)

Employee discount

Paid sick leave

Paid holidays

Paid vacation

Job summary

Target is seeking a Lead AI Engineer in Advanced AI to design, build, deploy, and maintain AI/ML applications across enterprise workflows. You will collaborate with data scientists, engineers, product partners, platform and security teams to turn ambiguous problems into scalable solutions.

You will provide hands-on technical leadership, help shape architecture, evaluate models and tools, and drive engineering practices, observability, and production readiness.

Qualifications

• 4-year degree in Quantitative disciplines or equivalent industry experience.
• 5+ years end-to-end applied ML and hands-on AI/ML experience.
• Experience building LLM-powered applications and agentic systems.
• Proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow).
• Experience with model APIs, prompt orchestration, retrieval-augmented generation, and cloud ML platforms.

Responsibilities

• Design, build, deploy, and maintain AI/ML applications across core workflows.
• Provide hands-on technical leadership and set engineering practices.
• Collaborate with data scientists, engineers, product partners, and security teams.
• Ensure secure, reliable, and production-ready AI systems aligned with enterprise standards.

Skills

Python programming

PyTorch

TensorFlow

LangChain

LlamaIndex

Semantic Kernel

Model APIs

Prompt orchestration

Agent development

Distributed systems

Education

B.S. in Quantitative disciplines

MS in CS/ML/AI preferred

Tools

Docker

Kubernetes

LangChain

LlamaIndex

Semantic Kernel

Job description

Target is seeking a Lead AI Engineer in Advanced AI to design, build, deploy, and maintain AI/ML applications across enterprise workflows. You will collaborate with data scientists, engineers, product partners, platform and security teams to turn ambiguous problems into scalable solutions.

You will provide hands-on technical leadership, help shape architecture, evaluate models and tools, and drive engineering practices, observability, and production readiness.