2 days ago
AI Quality Engineer (Contract)
Side · Hyderabad, Telangana, India
WorkableApply on company site
Contract
Onsite
Role overview
AI Quality Engineer
Location:- Hyderabad Work Mode:- WFO (5 days a week) Role Type:- Contractual (3 months and extension would depend on project requirement and performance)
Key Responsibilities
- Test and validate AI-generated insights, recommendations, and decision-making workflows.
- Evaluate LLM and RAG systems for accuracy, relevance, consistency, factuality, and hallucinations.
- Validate retrieval quality, context relevance, grounding, and response quality in RAG systems.
- Test AI agents and autonomous workflows across functional, negative, and edge-case scenarios.
- Define AI evaluation criteria, test datasets, quality metrics, and validation processes.
- Perform regression testing for models, prompts, RAG configurations, and AI workflows.
- Collaborate with AI/ML engineers to identify issues and improve AI system quality.
Requirements
Required Skills
- Strong understanding of AI/ML and Generative AI testing.
- Hands-on experience testing LLM and RAG-based applications .
- Knowledge of LLM evaluation, hallucination detection, relevance, and response quality.
- Understanding of AI agents and recommendation systems.
- Strong analytical and problem-solving skills.
Good to Have
- Experience with PyTest and automated testing frameworks.
- Experience building automated AI evaluation and regression frameworks.
- Familiarity with tools such as RAGAS, DeepEval, LangSmith, or equivalent.
- Experience with CI/CD-based test automation, performance testing, or AI guardrails.
- Familiarity with cloud platforms (AWS/Azure/GCP) and observability tools.
Success Metrics
- High accuracy, relevance, and reliability of AI outputs.
- Strong evaluation coverage across critical AI workflows.
- Early detection and reduction of hallucinations and AI regressions.
- Reduced production AI quality issues.
- Increased confidence and trust in AI-generated insights and recommendations.
Responsibilities
1Test and validate AI-generated insights, recommendations, and decision-making workflows.
2Evaluate LLM and RAG systems for accuracy, relevance, consistency, factuality, and hallucinations.
3Validate retrieval quality, context relevance, grounding, and response quality in RAG systems.
4Test AI agents and autonomous workflows across functional, negative, and edge-case scenarios.
5Define AI evaluation criteria, test datasets, quality metrics, and validation processes.
6Perform regression testing for models, prompts, RAG configurations, and AI workflows.
7Collaborate with AI/ML engineers to identify issues and improve AI system quality.
8AI Quality Engineer
Requirements
1Strong understanding of AI/ML and Generative AI testing.
2Hands-on experience testing LLM and RAG-based applications .
3Knowledge of LLM evaluation, hallucination detection, relevance, and response quality.
4Understanding of AI agents and recommendation systems.
5Strong analytical and problem-solving skills.
6Experience with PyTest and automated testing frameworks.
7Experience building automated AI evaluation and regression frameworks.
8Familiarity with tools such as RAGAS, DeepEval, LangSmith, or equivalent.
9Experience with CI/CD-based test automation, performance testing, or AI guardrails.
10Familiarity with cloud platforms (AWS/Azure/GCP) and observability tools.
11High accuracy, relevance, and reliability of AI outputs.
12Strong evaluation coverage across critical AI workflows.
13Early detection and reduction of hallucinations and AI regressions.
14Reduced production AI quality issues.
Skills and tags
Quality AssuranceINAWSAzureAIQA