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$
USD
I will engineer multi agent llm systems with rag pipelines and evaluations
Muhammad Wasim
About this gig
Turning an LLM into a working product fails at retrieval quality, agent reliability, and hallucinations not the prompt. That's what I fix.
I build production multi-agent LLM systems combining RAG, specialized agents, and deterministic verification layers for accurate, explainable output.
WHAT I BUILD
End-to-end RAG pipelines (ingestion, embeddings, vector search, grounded generation)
Multi-agent systems coordinated agents, not one overloaded prompt
Anti-hallucination verification layers
Evaluation frameworks precision/recall, faithfulness scoring, regression testing
FastAPI backends, deployment-ready
EXPERIENCE
Built a compliance-document validation platform (5 LLM agents, rule-verification) and a CV-to-JD matching system both shipped for real clients. Also fine-tuned Whisper/Wav2Vec2 for a defense R&D program.
STACK: LangGraph, LangChain, Hugging Face, PyTorch, FastAPI, vector DBs, Docker.
Message me your use case first I'll tell you honestly if this approach fits.
Get to know Muhammad Wasim
Muhammad Wasim
AI Engineer ! LLM and Speech AI Specialist
- FromPakistan
- Member sinceJan 2025
- Last delivery1 year
Languages
Urdu, English
I'm an AI Engineer who builds end to end LLM applications, from RAG pipelines to multi-agent systems with real evaluation and anti-hallucination checks built in.
I've built production systems for real clients, including a compliance document validation platform using 5 specialized agents with rule-based verification, and a CV to job description matching system. I also fine-tuned Whisper and Wav2Vec2 for a defense-sector speech recognition project.
I care about reliability over demos. If you need something that actually holds up in production, message me your use case.
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Other AI Development Services I Offer
FAQ
Do I need to already have my data/documents ready?
No — share what you have and I'll advise on data prep as part of the process.
Which LLM providers do you work with?
OpenAI, Anthropic (Claude), and open-source models via Hugging Face — I'll recommend the best fit for your budget and latency needs.
Can you evaluate an existing RAG/agent system I already built?
Yes, this can be scoped as a custom order — message me first.
What does "evaluation" actually include?
Retrieval precision/recall, hallucination/faithfulness scoring against source documents, and (for Standard/Premium) a repeatable test suite so you can catch regressions later.
