Open to opportunities

ubaid zafar

@ubaidzafar1

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AI Engineer building scalable backend systems with LLMs, RAG, multi-agent workflows, and production-grade evaluation.

Pakistan

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What I'm looking for

I’m looking to build production-ready LLM systems—RAG, multi-agent workflows, and evaluation/monitoring—backed by scalable backend services. I want opportunities to ship reliable, fast solutions and continuously improve factual accuracy in real deployments.

I’m an AI Engineer specializing in building scalable backend systems integrated with LLMs and agentic workflows. I focus on designing production-grade RAG pipelines, multi-agent architectures, and evaluation systems to help ensure reliability and factual accuracy.

Recently, as an AI/ML Engineer Trainee, I designed and deployed LLM-powered backend systems using LangGraph and MCP for production AI applications. I’ve built multi-agent workflows with dynamic tool routing, implemented DeepEval-based evaluation pipelines, and optimized distributed execution with Celery and Redis—always with real-world deployment, scalability, and performance in mind.

Experience

Work history, roles, and key accomplishments

Current

AI Engineer Trainee

Current

Allzone Technologies

Jan 2026 - Present (5 months)

Designed and deployed LLM-powered backend systems using LangGraph and MCP for production AI applications. Built multi-agent workflows and DeepEval-based evaluation pipelines to improve factual accuracy, citation reliability, and scalable background execution with Celery and Redis.

LangGraph Model Context Protocol (MCP)DeepEval Cross Encoder Re Ranking Celery Redis Multi Agent Pipelines

AI Prompt Engineer

Colossyan

Feb 2025 - Aug 2025 (6 months)

Engineered prompt templates and chaining workflows for AI video generation systems. Improved output consistency with structured prompting and few-shot techniques, and reduced manual revision cycles by building reusable prompt systems for production pipelines.

Prompt Generation AI Video Generation