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I will be red teaming safety evaluation for chatbots rag agent
Bharath
About this gig
I will red-team your AI chatbot for hallucinations, prompt injection and unsafe outputs
Description:
Before launch, someone needs to try to break your assistant. Ill do it methodically: prompt injection, jailbreaks, off-topic drift, PII leakage, fabricated citations, and domain-specific failure modes (medical, legal, financial). You get a severity-rated findings log with reproducible cases and mitigation guidance, plus a regression set so the fixes stay fixed.
Get to know Bharath
Bharath
LLM AI Model Evaluation Specialist , QA automation Architect ,Eval pipelines
- FromIndia
- Member sinceSep 2021
- Avg. response time1 hour
- Last delivery8 months
Languages
English, Tamil, Hindi
I help AI product teams answer one question: is this model actually good enough to ship? I built evaluation pipelines for LLM generated reports, validated models
Test consultant with 15+ years of professional experience and has expertise in QA for AI agents, Chatbots, RAGS, Web and mobile applications in domain like Banking, Insurance, Manufacturing, ecommerce. etc
* Expertise in automation testing using tool like Playwright, Selenium using Python, Java
* API testing using Postman
* Performance testing using Jmeter and K6 tools
* Security testing and Vulnerability assessment (OWASP standards)
Other AI Development Services I Offer
FAQ
Do I need to share my production data?
No. I work from samples you choose, synthetic data, or a redacted export. Everything stays under your NDA and is deleted on delivery.
Which eval tools do you use?
Promptfoo, LangSmith, Ragas, DeepEval, or a plain Python/pytest harness. I pick what fits your stack
Can you evaluate a RAG system or an agent, not just a single prompt?
Yes. For RAG I score retrieval and generation separately (context precision/recall, faithfulness, answer relevance). For agents I evaluate tool-call correctness and task completion.
What does "LLM-as-judge" mean and is it reliable?
A second model grades outputs against a rubric I write with you. I calibrate it against a human-labelled sample so you know how much to trust the scores.
Do you also do red-teaming or model comparison?
Yes — both are separate gigs on my profile, or add them as extras here.
