Architect

Experience: 8+ years IT (strong SDET foundation) + 3+ years dedicated AI, LLM, and Agentic system evaluation. Experience in a product-led organization or AI research lab is preferred.Role Overview

A strategic role driving AI, Advanced Quality Engineering, and Thought Leadership. Define evaluation models for LLM and Agentic workflow safety and reliability, combining traditional QA foundations with next-gen AI testing paradigms to lead niche skills groups.

Key Responsibilities

• Frameworks & Strategy: Build automated evaluation frameworks for LLMs, RAG pipelines, and Agentic workflows. Implement LLM-as-a-judge benchmarks, HITL, and tools like LangSmith, TruLens, DeepEval, Phoenix, and Ragas into CI/CD.
• Cloud & Agentic Infra: Deploy agentic frameworks (Perception/Reasoning/Action) in AWS, GCP, and Azure using containerization, service governance, and cloud orchestration.
• AI Evaluation: Validate functional output quality (hallucinations, relevance, tool-calling precision) and non-functional vectors (red-teaming, prompt injection, jailbreaking, toxicity, latency, cost).
• Upskilling & Presales: Mentor QA/SDETs into niche AI testing specialists. Support presales and drive market authority through articles and open-source benchmarks.
  
  

Required Skills & Qualifications

• Core SDET Mastery: Expert-level Java, Python, and Node.JS scripting. Advanced hands-on automation with Selenium, Playwright, RestAssured, Mobile testing (iOS/Android), and strong Manual testing foundations.
• AI/ML Expertise: Transformer architectures, Vector DBs (Pinecone, Milvus), fine-tuning, and frameworks like LangChain, LlamaIndex, or AutoGen.
• Metrics & MLOps: Experience with BLEU, ROUGE, G-Eval, BERTScore, Context Precision, and Faithfulness. Familiar with MLflow, Weights & Biases, and cloud infrastructure-as-code.