Victory A.

Agentic AI Engineer | AI Agents, LLM Agent, RAG, MCP & AI Applications

I build 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗔𝗜 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 that can understand 𝗰𝗼𝗻𝘁𝗲𝘅𝘁, retrieve 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲, use 𝘁𝗼𝗼𝗹𝘀, interact with 𝗔𝗣𝗜𝘀, make 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀, and take 𝗮𝗰𝘁𝗶𝗼𝗻𝘀. I am an Agentic AI Engineer specializing in 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, 𝗟𝗟𝗠 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, 𝗥𝗔𝗚, 𝗠𝗖𝗣, 𝗔𝗜 𝗦𝗮𝗮𝗦, and 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀. My focus is the engineering layer between an 𝗟𝗟𝗠 and a 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻. That means I do not just connect an LLM to a prompt and call it an AI agent. I design the architecture that allows an AI system to reason through a task, retrieve the right context, select and use tools, interact with external systems, maintain state, validate outputs, and escalate to a human when necessary. I have built 25+ AI agents, 5+ AI applications, 100+ n8n workflows, and worked with 7+ LLM models across different AI and automation use cases. What I build 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 & 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 AI agents with tool/function calling Autonomous and semi-autonomous agents Multi-step agent workflows Multi-agent systems and agent orchestration Planning, reasoning and execution loops Agent memory and state management Human-in-the-loop systems AI agents connected to business tools AI research and task-execution agents AI sales and customer-support agents 𝗟𝗟𝗠 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 Custom LLM-powered applications AI SaaS products AI copilots and assistants Conversational AI applications Structured LLM workflows Prompt and context engineering LLM routing and model selection Structured outputs and function calling AI-powered decision systems 𝗥𝗔𝗚 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 Retrieval-Augmented Generation (RAG) Document ingestion and processing Embeddings and semantic search Vector databases Knowledge bases Hybrid/contextual retrieval Chunking and metadata strategies Grounded AI responses Private company knowledge assistants RAG pipelines for internal and customer-facing applications 𝗠𝗖𝗣 & 𝗧𝗼𝗼𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 Model Context Protocol (MCP) MCP servers and tool integrations AI-to-tool communication Connecting agents to external data sources API and function-based tools Controlled access to business systems Tool discovery and execution 𝗔𝗜 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 AI web applications AI SaaS platforms AI dashboards and internal tools AI-enabled existing applications Backend AI services Database-connected AI systems AI APIs and microservices Authentication and application logic AI + frontend/backend integration AI & Development Stack I work across OpenAI, Claude, Gemini and other LLM platforms, with Python, JavaScript, APIs, webhooks, databases, and automation infrastructure depending on the architecture. My stack can include: 1. AI: OpenAI API, Claude, Gemini, LLMs, RAG, embeddings, vector search, AI agents, MCP 2. Backend: Python, FastAPI, Node.js, REST APIs, webhooks, PostgreSQL, Supabase 3. Application: React, Next.js, AI SaaS, web applications, dashboards and internal tools 4. Automation & orchestration: n8n, Make, API integrations, event-driven workflows 5. Voice AI: Vapi, Retell, Twilio, ElevenLabs 6. Business systems: GoHighLevel, HubSpot, Airtable, Google Workspace and other third-party platforms If you are building an AI product, agent, or intelligent workflow, I can help you go from “𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹 𝗰𝗮𝗻 𝗱𝗼 𝘁𝗵𝗶𝘀” to “𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗼 𝘁𝗵𝗶𝘀 𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝘆.” Send me your current architecture, workflow, or product idea. I will look at where the agent needs context, tools, memory, retrieval, APIs, and guardrails, and 𝗮𝗻𝗱 𝘄𝗲 𝗰𝗮𝗻 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗲 𝘁𝗵𝗲 𝘀𝗶𝗺𝗽𝗹𝗲𝘀𝘁 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝘁𝗼 𝗴𝗲𝘁 𝗶𝘁 𝘄𝗼𝗿𝗸𝗶𝗻𝗴.