Job Summary:

As a Prompt Engineer specializing in SaaS application testing, you will design and validate prompts used by large language models, assess AI system performance, and integrate generative AI into QA workflows. You’ll work across teams to embed AI tools into the software development lifecycle, enhancing testing efficiency, identifying issues proactively, and driving innovation through AI adoption.

Key Responsibilities:

Prompt Design & Evaluation

                  •               Create, test, and refine prompts used in AI-powered features of the SaaS platform.

                  •               Evaluate AI outputs for accuracy, consistency, bias, and alignment with business requirements.

                  •               Design edge case scenarios and stress tests to identify prompt/model failure modes.

AI-Driven QA Integration

                  •               Incorporate AI-based tools and techniques into automated and manual QA processes.

                  •               Use LLMs to generate test cases, validate UI/UX behavior, and identify potential bugs or inconsistencies.

                  •               Collaborate with QA and DevOps teams to embed AI models into CI/CD pipelines.

Strategic AI Adoption

                  •               Advocate for and lead the adoption of AI tools and workflows across engineering, QA, and product teams.

                  •               Evaluate AI tools, libraries, and APIs for integration into the dev/test toolchain.

                  •               Develop internal best practices, frameworks, and documentation for AI-assisted development and testing.

Cross-Functional Collaboration

                  •               Partner with Product Managers, QA Analysts, Data Scientists, and Engineers to improve model performance and user experience.

                  •               Communicate AI performance insights to stakeholders and contribute to roadmap discussions.

Qualifications:

                  •               2+ years of experience working with large language models or AI systems in production environments.

                  •               Strong understanding of prompt engineering concepts, generative AI behavior, and prompt evaluation techniques.

                  •               Hands-on experience integrating AI tools into QA workflows or software development processes.

                  •               Proficient in scripting or automation (e.g., Python, JavaScript, or Bash).

                  •               Familiarity with SaaS platforms, agile methodologies, and modern software delivery pipelines.

                  •               Ability to define and track performance metrics for AI-enhanced features and QA tools.

                  •               Experience driving cross-team initiatives or change adoption within a technical organization.

Desired Skills and Experience:

                  •               Experience with AI development platforms (OpenAI, Anthropic, Hugging Face, etc.).

                  •               Familiarity with AI safety, model robustness, prompt injection, and testing adversarial behavior.

                  •               Exposure to MLOps practices, LangChain, vector databases, or RAG systems.

                  •               Background in quality engineering, automation frameworks (e.g., Selenium, Cypress), or model evaluation pipelines.