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I will evaluate and optimize your llm or rag application
Jeet Majumder
About this gig
Is your LLM or RAG application workingbut not reliably, efficiently, or cost-effectively?
I help developers and businesses evaluate, monitor and optimize production AI systems.
I can analyze your LLM, RAG pipeline or AI agent for hallucinations, retrieval quality, response quality, token usage, latency, reliability and production performance.
Depending on your project, I can build evaluation pipelines, improve retrieval and prompts, optimize context and token usage, add LLM observability, implement regression testing, and help prepare your AI system for production.
Services include:
- LLM & RAG evaluation
- Hallucination & grounding analysis
- Retrieval evaluation
- Prompt & context optimization
- Token & cost optimization
- Latency optimization
- LLM observability & tracing
- Evaluation datasets & automated testing
- Production AI monitoring
- Docker / deployment support
Tools can include LangSmith, Ragas, DeepEval, MLflow, Docker, Python and cloud infrastructure depending on your system.
Have an existing AI application that needs to become more reliable and production-ready?
Send me your architecture or repository before ordering so I can recommend the appropriate scope.
Get to know Jeet Majumder
Jeet Majumder
AIML Engineer
- FromIndia
- Member sinceSep 2026
- Avg. response time1 hour
Languages
English, Bengali, Hindi
I am an AI/ML Engineer with 2+ years of experience building and deploying AI systems using Python, LLMs, RAG, and Agentic AI. I specialize in designing end-to-end retrieval pipelines, multi-agent workflows, and tool orchestration using LangGraph, FastAPI, and LangSmith to deliver reliable production-grade AI solutions.
My Portfolio
FAQ
What types of AI systems can you evaluate?
I can evaluate LLM applications, RAG systems, AI agents, chatbots and other AI applications that use language models.
Can you evaluate my existing RAG application?
Yes. I can evaluate retrieval quality, context relevance, grounding, answer quality and hallucination behavior.
Can you reduce my LLM API costs?
Yes. I can analyze token usage, prompts, context size, model selection, retrieval and request patterns and recommend or implement appropriate optimizations.
Can you add LangSmith or another observability solution?
Yes. Depending on your architecture, I can add tracing and monitoring for LLM calls, retrieval, tools, latency, errors and token usage.
Do I need an existing AI application?
For evaluation and optimization packages, yes. You should provide an existing LLM, RAG or AI-agent system.
Can you build an evaluation pipeline?
Yes. I can create evaluation datasets, automated evaluation workflows and regression tests appropriate to your application.
