AI QA Lead

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

Job summary

Robotics Technologies LLC in Weehawken, NJ seeks an AI QA Lead to own AI adoption, governance, and quality assurance across the QE lifecycle. The role focuses on Agentic AI, GenAI, LLM, RAG, and specification-driven testing, automation, validation, governance, and release assurance.

Responsibilities include leading AI-assisted requirement analysis, defining test scenarios, governing model validation, and delivering auditable QE outcomes with cross-functional collaboration across engineering and

Qualifications

• Minimum 15 years of Quality Engineering experience is mandatory.
• Expertise in QE strategy, test automation, and cross-functional delivery.
• Practical exposure to GenAI, LLM, RAG, or AI-enabled test automation.
• Experience with agile delivery, CI/CD practices, test governance, and enterprise SDLC.
• Bachelor’s degree in computer science, Information Technology, Engineering, or related field; master’s 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 behaviour checks and responsible-AI controls.
• Guide automation-ready assets, self-healing automation frameworks, orchestration, 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 to deliver QE outcomes.

Skills

QE strategy

Test automation

Stakeholder management

Cross-functional delivery

GenAI/Large Language Models

Agile delivery

CI/CD practices

Quality metrics

Executive communication

Education

Bachelor's degree in CS/IT/Engineering

Master's degree or QE/cloud/automation/AI certifications

Job description

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.