Lead AI Engineer – Advanced AI, Applied ML, LLMs, Agentic AI, ML Ops

Target

Lead AI Engineer designing and implementing AI/ML applications for Target's Advanced AI team. Collaborating with cross-functional teams to deliver scalable solutions focused on business value.

Posted 7/13/2026full-timeBrooklyn Park • California, Minnesota • 🇺🇸 United StatesSenior💰 $132,000 - $286,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI/ML applications, with a strong focus on architecture, security, and maintainability. Proficient in Python and modern AI frameworks, with a commitment to best engineering practices and collaboration across teams.

Highest-signal resume keywords

Applied Machine Learning ExperiencePython Programming ProficiencyAI/ML Frameworks (PyTorch, TensorFlow)Model API DevelopmentSystem Design and Application Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied Machine LearningAI/ML Application DevelopmentPython ProgrammingDeep Learning FrameworksModel APIsData PipelinesCI/CD PracticesPerformance OptimizationObservability ToolsVersion Control

Soft Skills

Strong Communication SkillsMentoringCollaborationSelf-DrivenResults-Oriented

Tools & Technologies

PyTorchTensorFlowLangChainLlamaIndexSemantic KernelCloud ML PlatformsContainersOrchestration TechnologiesOperational MonitoringDocumentation Tools

Industry Keywords

AI EngineeringMachine LearningAutomationData HandlingEnterprise StandardsTechnical LeadershipBusiness WorkflowsIntelligent AutomationScalable ServicesCross-Functional Collaboration

Tech Stack

Tools & technologies

CloudPythonPyTorchTensorflow

About the role

Key responsibilities & impact

help design, build, deploy, and maintain AI/ML applications that support automation, insight, and action across core business workflows
work closely with Data Scientists, engineers, product partners, platform teams, security teams, and business stakeholders
provide hands-on technical leadership for AI engineering initiatives
contribute to architecture and design decisions
evaluate appropriate models, frameworks, and tools
write maintainable production-quality code
establish strong engineering practices across development, testing, deployment, observability, documentation, and ongoing support
ensure AI applications are secure, reliable, maintainable, and aligned to Target’s enterprise standards for infrastructure, platform architecture, data handling, and operational readiness
partner with senior engineers and engineering leaders to shape technical approaches, identify implementation risks, resolve roadblocks, and support the evolution of reusable AI engineering patterns
stay current with developments in AI, machine learning, LLMs, agentic systems, and modern software engineering practices

Requirements

What you’ll need

4-year degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics) or equivalent industry experience required
5+ years end to end applied machine learning and of hands-on experience developing AI/ML applications
Experience building LLM-powered applications, agentic systems, applied machine learning solutions, data-intensive applications or intelligent automation capabilities
Demonstrated strong programming proficiency with Python and experience with modern AI/ML or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Semantic Kernel, etc.
Experience working with model APIs, prompt orchestration, agent development patterns, retrieval-augmented generation, evaluation frameworks, observability tools, cloud ML platforms, containers or orchestration technologies
Strong understanding of system design, application architecture, model and framework tradeoffs, experimentation, evaluation strategy, performance optimization and production deployment considerations for AI systems
Experience building scalable, maintainable, and well-tested services, APIs, data pipelines, applications or platforms
Experience with version control, CI/CD, code review practices, documentation, operational monitoring and production support
Ability to translate ambiguous business problems 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, applied data scientists, Product partners, business stakeholder and leaders
Ability to mentor AI engineers, contribute to technical direction and raise the quality of engineering practices within the 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 systems that create business value.

Benefits

Comp & perks

comprehensive health benefits and programs
medical
vision
dental
life insurance
401(k)
employee discount
short term disability
long term disability
paid sick leave
paid national holidays
paid vacation