I will build private ai agents and rag systems on your infrastructure


About this gig
Need AI that runs on your own infrastructure, with your data never leaving it, and guardrails a security team will sign off?
I'm Muhammad Omaid, Head of AI at Magnus Mage (est. 2019), 8+ years in production software, 10+ engineers behind me. Four AI systems in production: an on-device security agent, Bugshot vulnerability automation, the AI layer of Xyress and a multi-tenant AI CRM platform.
What we build:
RAG and agents over your documents, databases and APIs: custom embeddings, FAISS or pgvector, fast retrieval with tuned encoding and decoding.
FastAPI services from zero with Pydantic schemas, packaged in Docker containers built for large traffic.
Multi-tool agents with human approval before privileged actions, least-privilege tools and audit logging.
Private inference: open models on your GPUs via Ollama or vLLM; QLoRA fine-tuning when prompts are not enough.
Deployment on AWS, Kubernetes or on-prem with monitoring and evals; scaling on a custom quote.
What you get: source code, architecture note, eval report, walkthrough video and a bug-fix window.
No trading bots, no promised outcomes. Message us before ordering with your use case, data and hosting for a custom quote.
Get to know Muhammad Omaid
Head of AI at Magnus Mage, LLM RAG and fine tuned models
- FromPakistan
- Member sinceJun 2024
- Avg. response time1 hour
Languages
Urdu, English
My Portfolio
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FAQ
Can everything run on-premises or in my VPC?
Yes. Our default is open models (Llama, Qwen, Mistral) served on your GPUs or cloud, with data staying in your environment. Hosted APIs (OpenAI, Claude) are used only if you choose them.
What security controls do you build in?
Human approval before state-changing actions, least-privilege tool scoping, metadata-only model context (no secrets or request bodies), append-only audit logs, and prompt-injection tests. Mapped to OWASP guidance on request.
Do you fine-tune models or only use prompts?
Both. Prompting and RAG first; when that is not enough we run QLoRA fine-tuning on your data (our runs have cut training loss by about 95%). Fine-tuning is included in Premium or available as its own gig.
What happens if something breaks after delivery?
Every package includes a bug-fix window for the delivered scope: 7 days Basic, 14 days Standard, 30 days Premium. Ongoing maintenance is available as an extra or a retainer.
Do you take larger or long-term projects?
Yes. Most of our work is multi-month. Message us with the scope and we will send a custom offer with milestones.
Can you sign an NDA?
Yes. Send it through the Fiverr inbox before ordering and we will return it signed.

