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Position Overview
Fusion is a cloud-based 3D modeling, CAD, CAM, CAE, and PCB software platform for professional product design and manufacturing. We're looking for a motivated Software QA Engineer to join the Design Engineering QA team, focusing on testing and validating Large Language Model (LLM) features integrated into Fusion. This role will ensure the quality, accuracy, and reliability of AI-powered conversational and generative capabilities within the product.
This is a hybrid position in Pune, India. You will report to Senior Manager, SQA.
Responsibilities
Perform manual and automated testing for LLM-powered features to ensure response quality, accuracy, and consistency.
Design and execute test cases for prompt-response validation, including edge cases and adversarial inputs.
Identify and document LLM-specific issues such as hallucinations, inaccurate responses, and inconsistent outputs.
Test LLM safety and guardrails including content moderation, inappropriate response handling, and prompt injection prevention.
Validate LLM integration with Fusion workflows and features, ensuring seamless user experience.
Track and verify LLM behavior consistency across model updates and versions.
Develop automation scripts for LLM testing using in-house tools and frameworks.
Collaborate with development teams to ensure timely defect resolution.
Validate and reproduce customer-reported LLM issues.
Complete assigned testing tasks on time and report progress regularly.
Minimum Qualifications
Bachelor's degree in Computer Science, Software Engineering, or related field.
2+ years of software QA experience.
Basic understanding of LLM/AI concepts (prompts, tokens, model responses, context windows).
Experience with test case development and defect tracking.
Familiarity with Python or scripting languages for test automation.
Experience with bug tracking systems and test management tools.
Good analytical and problem-solving skills with attention to detail.
Ability to work effectively in cross-functional teams.
Can work independently on day-to-day activities.
Preferred Qualifications
Experience testing LLM or conversational AI applications (chatbots, AI assistants).
Familiarity with LLM evaluation concepts (response relevance, factual accuracy, coherence).
Experience with prompt engineering or prompt testing.
Knowledge of LLM safety testing (bias detection, content filtering, jailbreak prevention).
Hands-on experience with 3D CAD/CAE software (Fusion 360, Inventor, etc.).
Familiarity with API testing tools (Postman, REST clients).
Familiarity with Agile/Scrum development methodologies.
Experience with AI/ML testing frameworks or evaluation tools.
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