Full Stack AI Engineer

Vertex Service Partners•Charlotte, NC

16h•Hybrid

About The Position

We are seeking a Full Stack AI Engineer who combines strong software engineering fundamentals with applied AI creativity. This role plays a foundational part in shaping Vertex’s AI and automation strategy—architecting, building, and deploying intelligent tools that transform how our businesses operate. You will own full-stack development of AI-driven internal tools, partner directly with operators and business units, and help build Vertex’s internal culture of AI adoption. This role requires high ownership, strong execution, and a passion for building practical, real-world AI solutions.

Requirements

4–7+ years of professional experience in software engineering with modern web frameworks.
Proficiency in Python and TypeScript; experience with FastAPI/Django and React/Next.js.
Hands-on experience with LLMs, RAG systems, vector databases, and prompt engineering.
Familiarity with Snowflake or similar data warehouse technologies.
Experience building and deploying applications in a cloud environment (Azure preferred).
Strong ownership mindset with the ability to iterate quickly and deliver high-quality tools.
Ability to translate complex operational or business problems into simple, elegant solutions.
Excellent communication skills and comfort working directly with non-technical business users.

Responsibilities

Build AI-Powered Internal Tools Design, prototype, and deploy full-stack applications using FastAPI/Django and React/Next.js.
Develop AI features including chat assistants, retrieval workflows, summarization, and workflow automation.
Integrate APIs and data systems including OpenAI, LangChain, ServiceTitan, and Snowflake .
Architect and Scale Vertex’s AI Foundations Establish scalable patterns for APIs, cloud deployments, CI/CD, and front-end frameworks.
Implement reliable pipelines for retrieval-augmented generation (RAG), prompt management, vector storage, and model orchestration.
Build reusable libraries and architectural components to accelerate future AI initiatives.
Automate Operational Workflows Identify manual workflows across operations, sales, finance, and field teams; replace them with AI-enabled tools and automation.
Partner with FP&A, Data Engineering, and Operations to ensure data is modeled effectively to support automations.
Build intuitive interfaces and solutions designed for non-technical internal users.
Drive AI Culture Across the Organization Lead workshops, demos, and internal sessions on how to use AI tools effectively.
Build self-service templates and guided workflows to help business users adopt AI independently.
Create documentation and best practices for AI tooling across the organization.
Cross-Functional Collaboration Work closely with the VP of Technology and executive leadership to prioritize AI opportunities.
Translate ambiguous business problems into prototypes and production-ready solutions.
Communicate complex technical concepts clearly and simply to non-technical teams.