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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Ender-IT • Bengaluru, Karnataka, India
Role & seniority: AI QA Lead (player–coach, senior/lead level)
Location & work type: Bangalore, India • Full-Time Employee (FTE)
Stack/tools: GenAI systems; AI evaluation/test design; prompt engineering basics; adversarial/edge-case testing; regression/repeatability checks; collaboration with AI QA Program Managers, product and ML teams; mentoring junior engineers
Lead day-to-day AI QA execution across client and internal projects
Design, execute, and review AI test cases, prompt-based evaluations, adversarial tests, and regression checks
Guide AI QA engineers on test design quality, evaluation depth/coverage, and correct interpretation of AI outputs; review/evaluate results and reports before client delivery; drive continuous QA process improvement
5–8+ years in QA/testing roles; hands-on AI/ML/GenAI testing
Strong understanding of prompt engineering basics and AI failure modes (hallucinations, inconsistency, bias, drift)
Ability to mentor/review junior engineers; high attention to detail and quality
Experience with automated/semi-automated evaluation tools
Exposure to security, safety, or adversarial testing
Client-facing QA experience; scripting or data analysis familiarity
Location & work type: Bangalore, India • Full-time role (FTE)
AI QA Lead
Location: Bangalore- India FTE
AI QA Lead to provide hands-on technical leadership for AI evaluation and test execution across GenAI systems. This is a player–coach role. You will actively design, execute, and review AI evaluation scenarios while guiding AI QA engineers and ensuring consistency, rigor, and quality of outcomes. This is not a traditional manual QA lead role. The role requires a strong understanding of GenAI behavior, failure modes, and evaluation techniques, combined with disciplined execution and mentoring ability.
Key Responsibilities Lead day-to-day AI QA execution across client and internal projects
Must-Have Skills & Experience 5–8+ years of experience in QA or testing roles Hands-on experience testing AI, ML, or GenAI systems
Good-to-Have Experience with automated or semi-automated evaluation tools Exposure to security, safety, or adversarial testing Experience in client-facing QA roles Familiarity with scripting or data analysis
What Success Looks Like (6–12 Months) AI QA execution is consistent, repeatable, and trusted Junior engineers produce higher-quality evaluations Evaluation reports require minimal rework Feedback from QA meaningfully improves AI systems
Working Style & Expectations Hands-on and detail-oriented Comfortable working with evolving AI behavior Calm, structured, and methodical