AI QA Lead

Artifintech; Weehawken (NJ); In loco; USD 90.000 - 123.000; Tempo pieno

Descrizione del lavoro

Artifintech is seeking an AI QA Lead in Weehawken, NJ to own AI adoption, governance, and quality across the QE lifecycle. The role focuses on Agentic AI, GenAI, LLM, RAG, specification-driven testing, automation, governance, and release assurance, working with engineering, DevOps, security, and leadership to deliver reliable AI quality outcomes.

Minimum 15 years of QE experience, strong executive communication, and a proven track record in enterprise SDLC delivery are expected.

Competenze

• Bachelor’s degree in computer science, information technology, engineering, or a related technical discipline.
• 15+ years of QE experience with strategy, automation, and governance.
• Experience with GenAI, LLM, RAG, agentic AI systems and AI-enabled test automation.
• Experience with agile delivery, CI/CD, test governance, and enterprise SDLC delivery.
• Strong executive communication, mentoring, and governance discipline.

Mansioni

• Lead AI-assisted requirement analysis, risk identification, acceptance criteria, and test design.
• Drive AI-based generation of test scenarios aligned to customer requirements.
• Govern LLM, RAG, and agentic AI validation, model behaviour checks, data quality, and responsible-AI controls.
• Guide automation-ready assets, self-healing automation, intelligent CI/CD orchestration, and audit reporting.
• Define QE outcomes across test coverage, defect leakage, automation ROI, and release confidence.
• Engage stakeholders across customers, engineering, architecture, DevOps, security, compliance, and leadership.

Conoscenze

QE leadership

Test automation

GenAI

LLM

CI/CD

Stakeholder mgmt

Executive comms

Formazione

Bachelor's degree

Master's degree

QE certifications

Descrizione del lavoro

Job Title: AI QA Lead

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

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.