Lead Full-Stack Engineer Advanced AI

Lead Full‑Stack Engineer – Advanced AIPay and Benefits

The pay range is $ - $ Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications.

Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves.

• medical
• vision
• dental
• life insurance
• more

Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation.

• 401(k)
• employee discount
• short term disability
• long term disability
• paid sick leave
• paid national holidays
• paid vacation

Find competitive benefits from financial and education to well-being and beyond at

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

Target’s Advanced AI team builds end-to-end AI/ML systems that create meaningful business value across the enterprise. These systems may be powered by LLMs, classical machine learning, or deep learning models, and are designed as scalable, reliable, production-grade applications, including agentic architectures where they add clear value.

As a Lead Full-Stack Engineer for Advanced AI, you will help design, build, deploy, and maintain the application layers, services, APIs, and user experiences that bring AI/ML capabilities into core business workflows. You will work closely with AI/ML Engineers, Data Scientists, product partners, platform teams, security teams, and business stakeholders to turn complex AI capabilities into practical, intuitive, and scalable applications.

In this role, you will provide hands-on technical leadership for full-stack engineering initiatives across Advanced AI applications. You will contribute to architecture and design decisions, build maintainable production-quality code, design and develop APIs and services, create user-facing application experiences, and help establish strong engineering practices across development, testing, deployment, observability, documentation, and ongoing support.

You will help ensure applications are secure, reliable, accessible, performant, maintainable, and aligned to Target’s enterprise standards for infrastructure, platform architecture, data handling, and operational readiness.

You will also partner with AI/ML Engineers, Lead and Principal Engineers, and engineering leaders to shape technical approaches, identify implementation risks, resolve roadblocks, and support the evolution of reusable application patterns for AI-powered products.

This role requires strong product thinking, curiosity, and continuous learning, including staying current with modern full-stack engineering practices and developments in AI, LLM-powered applications, agentic systems, and enterprise AI patterns. A successful Lead Full-Stack Engineer will help deliver production-grade AI applications that create measurable business value while raising the technical quality and capability of the broader team.

• 4-year degree or equivalent experience
• 5+ years of hands-on software engineering experience, including experience building and operating production applications
• Strong experience building full-stack applications, including user-facing experiences, backend services, APIs, integrations, and data-driven workflows
• Strong proficiency with modern backend and frontend development
• Experience with Python is strongly preferred and experience with Type Script, JavaScript, Java, Kotlin or Go
• Experience with modern web application frameworks, API design, service-oriented architectures, data integration patterns, and production application development
• Experience building applications that integrate with AI/ML capabilities, including model APIs, LLM-powered workflows, retrieval-augmented generation, agentic systems, intelligent automation, or data science outputs
• Strong understanding of system design, application…