I will build autonomous ai agents


About this gig
Are you tired of fragile chatbots that hallucinate? Real automation requires deterministic, stateful multi-agent systems built for scale.
I am a Forward Deployed AI Engineer (M.S. in AI/ML) specializing in custom, autonomous AI ecosystems. I don't write basic scripts; I architect robust cognitive engines that drive real business ROI.
What I Build:
- Multi-Agent Systems: Collaborating AI swarms via LangGraph & LangChain for complex workflows.
- Enterprise RAG: High-throughput pipelines via Azure OpenAI & Qdrant to securely query private data.
- Seamless Integrations: Using Model Context Protocol (MCP) to bind agents to legacy APIs, CRMs, and data silos.
- Production Backends: Dockerized, fault-tolerant FastAPI endpoints ready for secure deployment.
Why Work With Me?
- Enterprise Scale: I lead the development of domain-specific cognitive engines for large corporations.
- Deep Tech: I build custom asynchronous frameworks (Spec-RAG) and optimize token efficiency.
- End-to-End Delivery: Complete consulting from initial workflow mapping to final deployment.
- Note: Custom AI requires precise architecture. Please message me before ordering to map out your exact solution!
Get to know Manoj Kumar
AI Engineer, Forward Deployed Engineer
- FromIndia
- Member sinceOct 2026
Languages
Telugu, English, Tamil, Hindi
FAQ
What is the difference between a standard chatbot and what you build?
Standard chatbots just return text based on a prompt. I build autonomous, multi-agent systems that actually take action. My agents can reason, route tasks, query your private databases, trigger internal APIs, and execute complex, multi-step business workflows.
Is my proprietary enterprise data secure?
Absolutely. I specialize in enterprise-grade architecture. I build RAG pipelines using secure vector databases (like Qdrant) and can route everything through private instances like Azure OpenAI or even local open-source models (like Llama) to ensure your data never leaks.
Do you build the front-end user interface (UI) as well?
My primary expertise is in robust backend AI engineering (building the cognitive engine, APIs, and Docker containers). However, I can integrate the backend with chat interfaces and custom UIs.
What is MCP (Model Context Protocol) and why do you use it?
MCP is the new industry standard for securely connecting AI models to your internal tools and data sources. I use it to bridge the gap between foundational LLMs and your specific legacy enterprise systems, ensuring stable and secure integrations rather than fragile, custom-coded workarounds.
What do you need from me to get started?
I need a clear description of the business workflow you want to automate, the data sources the AI will need to access, and your preferred deployment environment. Please message me before ordering so we can map out the technical architecture first!

