Lead Fullstack Engineer- Advanced AI

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.

6+ 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 TypeScript, JavaScript, Java, Kotlin, Go, or similar languages is helpful.

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 architecture, security, performance, scalability, reliability, accessibility, observability, testing, and production deployment considerations.

Experience building scalable, maintainable, and well-tested services, APIs, data pipelines, integrations, applications, or platforms.

Experience with version control, CI/CD, code review practices, documentation, operational monitoring, and production support.

Ability to translate ambiguous business and user needs into clear technical approaches and collaborate with cross-functional partners to deliver practical solutions.

Strong communication skills, with the ability to explain technical concepts clearly to engineers, AI/ML Engineers, Data Scientists, product partners, business stakeholders, and leaders.

Ability to mentor engineers, contribute to technical direction, and raise the quality of full-stack engineering practices within a team.

Self-driven and results-oriented, with strong ownership, sound judgment, and the ability to move quickly while maintaining high technical standards.

Collaborative team player with a commitment to continuous learning, knowledge sharing, and building reliable AI-powered applications that create business value.

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