Automation Agent Engineer
Há 6 dias
Overview
Join to apply for the Automation Agent Engineer (SDET + RAG/Prompt Engineering) role at Perform .
We’re looking for a forward-thinking Automation Agent Engineer—part seasoned SDET, part prompt engineer—who’s excited to bridge the gap between classic QA automation and AI-assisted workflows. In this hybrid role, you’ll help develop and refine a mini-RAG system that transforms manual test cases into intelligent, LLM-generated test skeletons. You’ll shape how context is retrieved, how prompts are designed, and how generated test code aligns with standards for our Java-based automation stack (RestAssured, Selenium, Cucumber, Screenplay). This is a hands-on, highly collaborative role where your decisions will directly affect the quality, consistency, and scalability of our AI-enabled testing pipeline.
What You’ll Do- Design and refine prompt templates and few-shot examples to guide the LLM toward generating high-quality test code.
- Collaborate on RAG logic , including chunking strategies, metadata filters, and reranker tuning for optimal context retrieval.
- Help convert manual test cases into structured test skeletons , normalizing them to project standards.
- Build evaluation loops to validate generated code—ensuring compliance with naming, format, assertions, lint rules, and compile/run requirements.
- Review and land autoscripted code with proper guardrails , documentation, and handoff to the SDET team.
- Optimize token usage and latency while maintaining test fidelity in collaboration with the AI and QA teams.
- 5+ years of experience in QA automation with strong skills in Java , RestAssured , Selenium , Cucumber , and ideally the Screenplay pattern.
- Hands-on knowledge of prompt engineering , including few-shot prompting and structured output design.
- Working understanding of RAG concepts (embeddings, retrievers, rerankers) and how they apply to software development workflows.
- Familiarity with CI pipelines (Jenkins), Git workflows, and code review best practices.
- Experience with LangChain , ChromaDB , or other local retrieval systems.
- Understanding of LLMs like Claude 4 Sonnet and how to manage token/cost trade-offs.
- Ability to build small tools such as static analyzers, linters, or rule-based code evaluators.
- Not Applicable
- Other
- Sales and Business Development
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