llm qa

Key Responsibilities

Test Planning & Execution

Design and execute comprehensive test plans for applications integrating LLMs and AWS services.

Validate data pipelines, model outputs, APIs, and user interfaces with a focus on LLM-driven features such as text generation, summarization, and classification.

LLM Quality & Evaluation

Develop test cases for LLM responses, ensuring accuracy, relevance, consistency, and compliance.

Evaluate prompt quality, model outputs, and fine-tuned model behavior using both manual and automated techniques.

Support RAG pipelines and validate integration with vector databases or knowledge sources.

Automation & Tooling

Build and maintain automated test suites for backend services and LLM workflows using tools like PyTest, Postman, Selenium, or Playwright.

Integrate tests into CI/CD pipelines (e.g., using GitHub Actions, Jenkins, or CodePipeline).

AWS Integration Testing

Test cloud-native services and workflows built with AWS tools such as:

Lambda, S3, API Gateway, Step Functions, Bedrock, SageMaker, CloudWatch

Validate infrastructure-as-code using CloudFormation or CDK in test environments.

Performance, Security & Compliance Testing

Conduct performance testing of LLM APIs (e.g., latency, throughput, model fallback behavior).

Ensure compliance with data privacy, audit, and security standards when using LLMs in production workflows.

Collaboration & Documentation

Work closely with engineers, data scientists, and product managers to define quality metrics for LLM use cases.

Document test strategies, bug reports, and QA process improvements.

Technical Skills

5+ years of experience in software or data quality assurance.

Hands-on experience testing applications built on AWS (Lambda, S3, API Gateway, CloudWatch, Step Functions, etc.).

Experience testing or validating LLM-powered features (e.g., OpenAI, Amazon Bedrock, HuggingFace, Claude).

Strong skills in test automation (e.g., PyTest, Selenium, REST API testing).

Good understanding of CI/CD and DevOps in AWS environments.

Experience with Python or JavaScript/TypeScript for test scripting.

Nice to Have

Familiarity with LLMOps, prompt testing frameworks, or prompt injection scenarios.

Experience with LangChain, RAG patterns, or vector databases (e.g., Pinecone, FAISS).

Exposure to model evaluation metrics (e.g., BLEU, ROUGE, factual consistency).

Basic knowledge of data pipelines, ETL, or analytics workflows.

Preferred Experience

Testing GenAI or AI-enhanced applications in real-world environments.

Ensuring ethical AI usage, data privacy, and compliance in AI workflows.

Familiarity with monitoring LLM behaviour in production and logging tools.

About Virtusa

Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.

Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.

Virtusa was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.