Principal Agentic AI Engineer

About VF Corporation

Founded in 1899 and headquartered in Denver, Colorado, VF Corporation is one of the world’s largest apparel, footwear, and accessories companies. VF’s portfolio includes The North Face, Vans, Timberland, Altra, Smartwool, Icebreaker, Kipling, Napapijri, Eastpak, and JanSport. VF markets its products across the Americas, EMEA, and Asia‑Pacific through wholesale partnerships, branded retail stores, and a growing direct‑to‑consumer ecommerce ecosystem.

Agentic AI represents a critical acceleration capability – enabling VF to automate complex workflows, augment human decision‑making, and create intelligent systems across every function and every touchpoint.

Position Summary

The Principal Agentic AI Engineer is a hands‑on technical leader embedded in VF Corporation’s centralized Agentic AI team, a cross‑brand, cross‑region Center of Excellence that builds and deploys AI agents for every brand and function.

Key mandates:

1. Own the pro‑code development of production‑grade agentic AI, building custom agents, multi‑agent orchestration, complex integrations, and bespoke solutions.
2. Evangelize and enable low‑code development across brands and business functions, empowering citizen developers while establishing guardrails, patterns, templates, and governance.

Platform Polyglot: Choose the right agent platform and framework for each job (e.g., Copilot Studio, Azure AI Foundry).
Governance by Design: Build guardrails into every template, connector, and training to ensure safe decentralized agent creation.

Core Platform Responsibilities

Microsoft Copilot Studio — Low‑Code Enablement & Pro‑Code Extension

• Own the pro‑code extension layer: build custom connectors, develop Power Platform dataflows and custom actions, create reusable component libraries.
• Implement advanced Copilot Studio capabilities: multi‑agent orchestration, Model Context Protocol (MCP) server integration, human‑in‑the‑loop (HITL) approval workflows, and Copilot tuning.
• Build and enforce governance standards: lifecycle management, naming conventions, environment management, DLP policies, Entra Agent ID configuration, telemetry & analytics, cost tracking.
• Develop integration between Copilot Studio and Azure AI Foundry, creating seamless upgrade paths for agents that outgrow Copilot Studio.

Azure AI Foundry — Custom Agentic Application Development

• Architect and build production‑grade custom agentic applications using Azure OpenAI Service, Azure AI Search, Azure AI Agent Service, Prompt Flow, and Semantic Kernel.
• Build and maintain VF’s custom RAG pipelines and vector databases; develop agent evaluation and testing infrastructure (task‑specific benchmarks, LLM‑as‑judge pipelines, red‑team testing harnesses, regression test suites).
• Implement agent observability, tracing, monitoring, Application Insights, and custom telemetry for real‑time visibility into performance, cost, error rates, and impact.
• Contribute to responsible AI practices: guardrails, content safety filters, PII detection & masking, prompt‑injection defenses, bias mitigation.

Low‑Code Evangelism & Citizen Developer Enablement

• Design and deliver tiered training for Copilot Studio (Foundational, Intermediate, Advanced).
• Build and publish VF’s “Agent Developer Guide” and an agent template gallery (pre‑built, governance‑approved patterns, connector libraries, testing standards, deployment checklists).
• Track and govern developer adoption metrics: count, usage, business value delivered, and quality/governance compliance rates.
• Identify citizen‑built agents that hit low‑code limits and transition them to pro‑code solutions (custom connectors or migration to Azure AI Foundry).

Technical Responsibilities

Architecture & Design

• Design integration layer between VF’s agent platforms and enterprise systems of record (custom connectors, APIs, MCP servers, event‑driven architectures).
• Architect secure, performant RAG pipelines with proper chunking, embedding, indexing, and retrieval strategies.
• Establish standards for agent memory, state management, and context handling across short‑lived conversations and long‑running autonomous workflows.

Development & Delivery

• Write production‑quality code (TypeScript, Python, C#) for custom agents, orchestration logic, tool integrations, evaluation pipelines, and deployment automation on Azure AI Foundry.
• Build and maintain CI/CD pipelines for agent development across Copilot Studio and AI Foundry; develop custom connectors and MCP servers exposing enterprise systems to agents.
• Implement comprehensive agent testing: unit tests, integration tests, evaluation tests (LLM‑as‑judge, human review), and performance testing.

Governance & Quality

• Define and enforce agent quality standards (accuracy, hallucination tolerance, response SLAs, cost, brand voice).
• Implement governance automation for Copilot Studio (DLP policies, Entra Agent ID enforcement, environment controls, publishing approval workflows, automated compliance scanning).
• Build VF’s agent observability stack: dashboards showing health, usage, cost, quality scores, escalation rates, and business impact.
• Own incident response for production agent issues: rapid diagnosis, remediation, root‑cause analysis, post‑incident improvements.

Qualifications

Required

• 8+ years of software engineering experience (Senior) or 12+ years (Principal), with at least 2 years focused on AI/ML systems, conversational AI, or agentic AI platforms.
• Deep hands‑on expertise with Copilot Studio (low‑code authoring and pro‑code extension).
• Strong production experience with Azure AI Foundry (Azure OpenAI Service, Azure AI Search, Prompt Flow, Semantic Kernel, Azure AI Agent Service).
• Proficiency in at least two additional agent frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI).
• Deep understanding of agentic AI patterns: multi‑agent orchestration, tool‑use/function calling, RAG architectures, embedding strategies, evaluation methodologies, guardrails, MCP.
• Strong software engineering fundamentals: TypeScript, Python, or C#; RESTful and GraphQL API design; event‑driven architectures; CI/CD; IaC (Bicep, Terraform); containerization.
• Excellent communication skills for presenting to engineering peers and business leaders.
• Bachelor’s degree in Computer Science, AI/ML, Engineering, or related field (Master’s preferred).
• Experience with Sierra AI or comparable platforms for consumer‑facing customer service agents.
• Background in Power Platform administration, governance, and toolkit deployment.

Hiring Range

• $144,000.00 USD – $180,000.00 USD annually

Incentive Potential

• Eligible for additional compensation awards (annual incentive plan, sales incentive, or commission potential). Details provided during recruiting and interview process.

Benefits

• Comprehensive medical, dental, and vision plans (see www.MyVFbenefits.com for current rates).
• Additional benefit programs and detailed information provided during the hiring process.