Athenaworks Llc
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 url, - Use that data to automatically populate and modify website templates, - Generate or rewrite SEO-optimized content, - Reduce onboarding time and increase website production scalability. Key Responsibilities
Conversational AI & RAG
- 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. Web Content Understanding & Data Structuring
- Automate the extraction of business details, products, design elements from public website using GenAI - Normalize and structure this data for downstream systems like Salesforce, CMS, and web template engines. Generative Web Template Modification
- Build AI-driven tools to modify HTML/CSS templates based on onboarding inputs: • Replace content tokens • Update colors/fonts/images using structured data • Insert/rewrite sections (e.g. hero banners, testimonials) using LLM-generated content - Guide LLMs to edit existing HTML blocks or JSON-configurable component files intelligently. SEO-Aware Content Generation
- Generate/rewrite homepage headlines, service blurbs, and metadata with an SEO-first approach. - Ensure AI-generated content is unique and plagiarism-free. Technical Skills & Requirements
Must-Have
- Strong experience with LLMs (OpenAI GPT-4, Claude, Cohere, etc.) for RAG and generation tasks - Experience building RAG pipelines using tools like: • LangChain, LlamaIndex, Haystack, or custom solutions • Vector DBs (e.g. Pinecone, Weaviate, FAISS) - Experience in building Agentic flows using tools like 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) Preferred
- 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, TypeScript, or similar Example Projects You Might Work On
- 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 Collaborates With
- Full Stack Developers (template rendering, CMS integration) - Content Strategists (prompt tuning, SEO optimization) - UX Designers (branding consistency, component mapping) - DevOps (pipeline automation for content + templates)
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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 url, - Use that data to automatically populate and modify website templates, - Generate or rewrite SEO-optimized content, - Reduce onboarding time and increase website production scalability. Key Responsibilities
Conversational AI & RAG
- 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. Web Content Understanding & Data Structuring
- Automate the extraction of business details, products, design elements from public website using GenAI - Normalize and structure this data for downstream systems like Salesforce, CMS, and web template engines. Generative Web Template Modification
- Build AI-driven tools to modify HTML/CSS templates based on onboarding inputs: • Replace content tokens • Update colors/fonts/images using structured data • Insert/rewrite sections (e.g. hero banners, testimonials) using LLM-generated content - Guide LLMs to edit existing HTML blocks or JSON-configurable component files intelligently. SEO-Aware Content Generation
- Generate/rewrite homepage headlines, service blurbs, and metadata with an SEO-first approach. - Ensure AI-generated content is unique and plagiarism-free. Technical Skills & Requirements
Must-Have
- Strong experience with LLMs (OpenAI GPT-4, Claude, Cohere, etc.) for RAG and generation tasks - Experience building RAG pipelines using tools like: • LangChain, LlamaIndex, Haystack, or custom solutions • Vector DBs (e.g. Pinecone, Weaviate, FAISS) - Experience in building Agentic flows using tools like 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) Preferred
- 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, TypeScript, or similar Example Projects You Might Work On
- 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 Collaborates With
- Full Stack Developers (template rendering, CMS integration) - Content Strategists (prompt tuning, SEO optimization) - UX Designers (branding consistency, component mapping) - DevOps (pipeline automation for content + templates)
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