AI QA Lead

Cloud Analytics Technologies, LLC; Weehawken (NJ); On-site; USD 88,000 - 125,000; Full time

Job summary

Cloud Analytics Technologies, LLC in Weehawken, NJ seeks an AI QA Lead to own AI adoption, governance, and quality across the QE lifecycle. The role emphasizes agentic AI, GenAI, LLM, RAG, and specification-driven testing with automation and governance.

Responsibilities include defining risk, designing test scenarios, validating AI models, and delivering auditable QE outcomes while collaborating with engineering, DevOps, and security teams.

Qualifications

• Minimum 15 years of Quality Engineering experience required.
• QE strategy, test automation, and cross-functional delivery experience are essential.
• Practical exposure to GenAI, LLM, RAG, or AI-enabled test automation is desired.
• Experience with agile delivery, CI/CD, test governance, and enterprise SDLC is expected.
• Bachelor's degree in a technical field is mandatory; master's and related certifications are preferred.

Responsibilities

• Lead AI-assisted requirement analysis, risk identification, acceptance-criteria definition, and specification-driven test design.
• Drive AI-based generation of test scenarios aligned to customer requirements.
• Govern LLM, RAG, and agentic AI validation including model behavior checks and hallucination validation.
• Guide automation-ready assets, self-healing automation frameworks, CI/CD orchestration, and audit-ready reporting.
• Define QE outcomes across test coverage, defect leakage, automation ROI, release confidence, and delivery efficiency.
• Engage with customers, engineering, architecture, DevOps, security, compliance, and leadership to deliver QE outcomes.

Skills

QE strategy

Test automation

Customer-facing leadership

Stakeholder management

Cross-functional delivery

Education

Bachelor's degree in computer science/IT/Engineering

Master's degree and relevant QE, cloud, automation, or AI certifications preferred

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AI QA Lead

Location: Weehawken, NJ

Duration: 8 Months + Extension

Bill Rate: $77/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

The AI-Native Quality Engineering Lead will own AI adoption, governance, and quality assurance across the end-to-end Quality Engineering lifecycle. The role focuses on Agentic AI, GenAI, LLM, RAG, specification-driven testing, automation, validation, governance, and release assurance.

Key Responsibilities:

• Lead AI-assisted requirement analysis, risk identification, acceptance-criteria definition, and specification-driven test design.
• Drive AI-based generation of positive, negative, edge-case, and business-rule-driven test scenarios aligned to customer requirements.
• Govern LLM, RAG, and agentic AI validation, including model behaviour checks, hallucination validation, data quality, traceability, and responsible-AI controls.
• Guide automation-ready assets, self-healing automation frameworks, intelligent CI/CD orchestration, quality gates, and audit-ready reporting.
• Define measurable QE outcomes across test coverage, defect leakage, automation ROI, release confidence, and delivery efficiency.
• Engage with customers, engineering, architecture, DevOps, security, compliance, and leadership stakeholders to deliver business-aligned QE outcomes.

Experience and Qualifications:

• Minimum 15 years of overall Quality Engineering experience is mandatory.
• Strong experience in QE strategy, test automation, customer-facing solution leadership, stakeholder management, and cross-functional delivery.
• Practical exposure to GenAI, LLM, RAG, agentic AI systems, AI evaluation, prompt engineering, or AI-enabled test automation.
• Experience with agile delivery, CI/CD practices, test governance, quality metrics, and enterprise SDLC delivery is expected.
• Bachelor's degree in computer science, Information Technology, Engineering, or a related technical discipline is mandatory; master's degree and relevant QE, cloud, automation, or AI certifications are preferred.
• Strong executive communication, mentoring capability, governance discipline, and ability to deliver reliable, auditable, business-aligned AI Quality Engineering outcomes.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.

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