bebo Technologies is a leading complete software solution provider. bebo stands for 'be extension be offshore'. We are a business partner of QASource, inc. USA [www.QASource.com].We offer outstanding services in the areas of software development, sustenance engineering, quality assurance and product support. bebo is dedicated to provide high-caliber offshore software services and solutions.
Our goal is to 'Deliver in time-every time'.
For more details visit our website: www.bebotechnologies.com
Let's have a 360 tour of our bebo premises by clicking on below link:
https://www.youtube.com/watch?v=S1Bgm07dPmM
Job Responsibilities
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Design, develop, and maintain automation frameworks using Python for AI and backend systems
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Perform Quality Engineering (QE) for AI/ML and RAG-based systems, ensuring accuracy, performance, and reliability
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Develop test strategies for LLM pipelines, prompt workflows, embeddings, vector databases, and retrieval mechanisms
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Validate AI workflows built using LangChain and LangGraph
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Perform functional, integration, regression, and performance testing for AI-powered applications
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Create test data, mock services, and validation metrics for AI responses and outputs
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Collaborate with cross-functional teams to identify test gaps and improve test coverage
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Integrate automated tests into CI/CD pipelines
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Ensure quality best practices across the SDLC for AI and non-AI components
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Document test plans, test cases, automation results, and defect reports
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B.Tech / B.E / MCA in Computer Science or related field
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2–5 years of experience as an SDET / QE / Automation Engineer
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Strong hands-on experience with Python automation
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Proven experience in Quality Engineering for AI systems, especially RAG architectures
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Hands-on exposure to LangChain and LangGraph for AI workflow orchestration
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Experience testing LLM-based applications and AI models
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Good understanding of software testing methodologies, QA processes, and best practices
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Experience with REST APIs, backend testing, and data validation
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Familiarity with version control systems like Git
Good to Have
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Experience with vector databases (e.g., FAISS, Pinecone, Chroma, Weaviate)
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Understanding of embeddings, prompt engineering, and LLM evaluation metrics
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Exposure to cloud platforms (AWS, Azure, or GCP)
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Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.)
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Knowledge of performance and load testing tools
