Senior AI Engineer | Generative AI, LLMs, Production RAG & Multi-Agent Workflows

About this Gig

I am a Senior AI Engineer(8+ years) specializing in designing, building, and deploying production-grade Generative AI, Retrieval-Augmented Generation (RAG), and Multi-Agent workflows. I bridge the gap between foundation models and autonomous action to build secure, intelligent systems that drive measurable business impact. Whether you need to automate manual operational workflows, build customer-facing assistants, or connect complex enterprise databases to secure LLM pipelines, I deliver robust backend architectures built for scale. My Core Technical Expertise Includes: AI Workflow Automation: Designing intelligent multi-agent systems (using LangGraph/LangChain) that turn natural language inputs into structured workflows, automated database updates, or enterprise business insights. Production RAG Architectures: Implementing meaning-based Retrieval-Augmented Generation with advanced semantic search, token-efficient chunking, and source-citation frameworks to eliminate model hallucinations. Conversational AI & Omnichannel Chatbots: Building enterprise bots capable of intent analysis, lead capture, and graceful human-agent handoffs across web widgets, WhatsApp Business API, and voice channels. Foundation Model & MLOps Integration: Deploying, evaluating, and fine-tuning models on cloud ecosystems (like Azure OpenAI and Supabase), ensuring high observability, robust rate-limiting, and multi-tenant data isolation. Proven Products I Have Built: VaaniAPI.com: An API-first, multi-tenant conversational AI customer support platform. It features an end-to-end RAG pipeline, providing context-aware, source-cited responses with automated lead capture and instant escalation to human agents.

Requirements

To ensure a seamless project kickoff and deliver an optimized AI solution tailored to your exact business objectives, I require the following information and materials from your team: Project Goal & Scope: A brief summary of what you want the AI assistant or automation to achieve (e.g., answering customer support questions, scraping and analyzing data, capturing marketing leads, or executing multi-step internal tasks). Knowledge Base & Core Data: The documentation, text files (PDF, DOCX, TXT), database structures, or URLs that the AI needs to read from. Please specify if this data updates dynamically or remains static. Deployment Channels & API Access: A list of the specific platforms where your customers or team will interact with the system (e.g., embeddable website widget, WhatsApp Business, Slack, or internal portals) along with necessary sandbox/API access keys. Handoff & Safety Protocol Rules: Your guidelines for out-of-scope questions. What should the bot say if a user asks something outside its knowledge base? At what point should the bot trigger an automatic transfer to a human support agent? Preferred Tech Stack & Infrastructure: Details regarding your current cloud environment (e.g., Azure, AWS, Supabase, Vector DB preferences) if you have an existing system you want me to integrate into.

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