AI Engineer

AI Engineer – RAG Systems & Generative Web Automation Role Summary

We are seeking a highly skilled AI Engineer with experience in Retrieval‑Augmented Generation (RAG) and Generative AI for Web Automation. This role will be responsible for building intelligent systems that:

• Collect and verify onboarding data from clients using conversational AI and fetching contents from URLs.
• Use that data to automatically populate and modify website templates.
• Generate or rewrite SEO‑optimized content.
• Reduce onboarding time and increase website production scalability.

• Build and refine a multi‑turn conversational agent (chatbot) to guide users through the onboarding process.
• Use RAG techniques to pull context from:
  • the dealer’s existing website
  • internal documentation/templates
  • knowledge bases (e.g., manufacturer data, SEO content ideas)
• Enable context‑aware LLM prompting to dynamically query and synthesize answers and suggestions.

• Automate the extraction of business details, products, and design elements from public websites using GenAI.
• Normalize and structure this data for downstream systems such as Salesforce, CMS, and web template engines.

• Build AI‑driven tools to modify HTML/CSS templates based on onboarding inputs:
  • Replace content tokens
  • Update colors, fonts, and images using structured data
  • Insert or rewrite sections such as hero banners and testimonials using LLM‑generated content
• Guide LLMs to edit existing HTML blocks or JSON‑configurable component files intelligently.

• Generate or rewrite homepage headlines, service blurbs, and metadata with an SEO‑first approach.
• Ensure AI‑generated content is unique and plagiarism‑free.

• Strong experience with LLMs (OpenAI GPT‑4, Claude, Cohere, etc.) for RAG and generation tasks.
• Experience building RAG pipelines using tools like:
  • Lang Chain, Llama Index, Haystack, or custom solutions
  • Vector databases (e.g., Pinecone, Weaviate, FAISS)
• Experience in building Agentic flows using tools such as Crew AI.
• Solid understanding of prompt engineering and context management.
• Ability to manipulate or generate HTML/CSS templates via AI or structured code editing.
• Proficiency in Python and associated ML/NLP libraries.
• Familiarity with schema‑based content generation (e.g., structured JSON to Liquid/HTML).

• Experience in fine‑tuning open‑source LLMs (e.g., using LoRA, PEFT).
• Familiarity with CMS platforms or static site generators (e.g., Webflow, Sanity, Hugo, etc.).
• Experience building chatbot interfaces using React, Type Script, or similar.

• AI module that scrapes a dealer’s website and maps content to the CMS schema.
• GPT‑4 agent that generates personalized homepage copy using the dealer’s product list.
• RAG‑enabled chatbot that provides theme suggestions based on scraped design cues.
• AI system that modifies Tailwind/HTML templates to match brand colors and layout preferences.

• Full Stack Developers (template rendering, CMS integration)
• Content Strategists (prompt tuning, SEO optimization)
• UX Designers (branding consistency, component mapping)
• Dev Ops (pipeline automation for content + templates)