Principal AI Engineer, Agentic Systems

Vuori•Carlsbad, CA

12h

About The Position

As a Principal AI Engineer specializing in Agentic Systems, you will own the design, development, and scaling of AI-powered applications, agentic systems, and intelligent tooling that enhance Vuori's operations. You will partner with business and technology leaders to identify high-value opportunities, develop production-ready AI solutions, and drive adoption of capabilities that improve efficiency, augment decision-making, and streamline complex business processes. You will set Vuori's AI platform strategy and develop reusable AI services, orchestration patterns, and engineering standards. You will build autonomous and human-in-the-loop solutions, including AI assistants, workflow orchestration, multi-agent systems, and custom AI applications. The role combines technical expertise, systems thinking, cross-functional collaboration, and business acumen to deliver measurable value for employees, customers, and business operations. You will define the evolution of Vuori's AI platform and technical standards; elevate engineering capability through reviews, pairing, and useful tools; make and defend build-versus-buy decisions; bring clarity to ambiguous problems, including determining when a workflow should not be agentic; and establish best practices for AI development, testing, evaluation, monitoring, observability, reliability, governance, security, and guardrails. You will design, build, and deploy AI applications, intelligent agents, and workflows; integrate LLMs with enterprise data, APIs, and business systems; build scalable orchestration, RAG, and knowledge retrieval architectures; and move promising capabilities from prototype to production. You will also identify opportunities with organizational partners, monitor performance, measure business impact, and improve results using data and feedback.

Requirements

10+ years of software engineering experience, including 2+ years building and operating production AI systems.
Demonstrated experience building and operating production agentic systems involving planning, reasoning, memory, and tool-calling.
Demonstrated experience designing and implementing AI evaluation frameworks, testing methodologies, and production monitoring to validate accuracy, reliability, safety, and business performance in real-world operational environments.
Strong proficiency in Python.
Experience building APIs, backend services, and cloud-native applications.
Deep experience with modern LLM platforms and orchestration frameworks, with the judgment to choose between them.
Experience integrating AI systems with enterprise APIs, databases, SaaS platforms, and business systems.
Strong analytical, problem-solving, and communication skills, including the ability to translate business needs into scalable technical solutions.

Nice To Haves

Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related technical field, or equivalent years of experience (listed as preferred).
Experience with RAG architectures, vector databases, embeddings, and enterprise knowledge retrieval systems.
Experience with low-code and pro-code enterprise AI platforms such as Azure AI Foundry, Google Gemini Enterprise, Microsoft Agent 365, or Copilot Studio.
Experience with Azure, AWS, or Google Cloud Platform.
Experience with AI observability, governance, security, and compliance frameworks.
Familiarity with MLOps, model lifecycle management, and AI deployment pipelines.
Experience in retail, direct-to-consumer, ecommerce, or a similar consumer operating environment.
Demonstrated passion for emerging AI technologies and applied innovation.

Responsibilities

Set the direction for Vuori's AI platform and define technical standards as the AI ecosystem matures.
Raise engineers' technical capabilities through review, pairing, and adoption of effective tooling.
Make and defend build-versus-buy decisions that shape the AI platform.
Clarify poorly defined problems and determine when a workflow should not use an agentic approach.
Establish engineering best practices for AI development, testing, evaluation, monitoring, observability, and reliability.
Implement governance, security, and guardrails for responsible and trustworthy AI solutions.
Design, build, and deploy AI-powered applications, intelligent agents, and agentic workflows addressing high-impact business challenges.
Develop systems using planning, reasoning, memory, and tool usage to automate or augment complex business processes.
Integrate LLMs, enterprise data sources, APIs, and business systems to deliver end-to-end AI experiences.
Build and maintain scalable agent orchestration, RAG, and knowledge retrieval architectures.
Prototype emerging AI capabilities and translate concepts into production-ready solutions.
Partner with business and technology leaders to identify opportunities for measurable AI-driven business value.
Monitor solution performance, measure business impact, and continuously improve outcomes using data and feedback.