Lead QA Engineer

Siri InfoSolutions Inc; Charlotte (NC); On-site; USD 110,000 - 150,000; Full time

Job summary

Siri InfoSolutions Inc is seeking a QA Engineer in Charlotte, NC for a full-time role focusing on testing AI applications, RAG systems, agents, APIs, and data pipelines. The candidate will design end-to-end test plans for generative AI and ML models, validate model performance, and lead automation efforts across teams.

Applicants should have 8+ years of experience in QA, a CS degree, and strong Python/PyTest skills to build robust automation frameworks and ensure data quality and system

Qualifications

• Bachelor's or master's degree in computer science or related field.
• 8+ years of experience in software quality assurance or test automation.
• Experience testing generative AI, ML models, and AI frameworks.
• Proven ability to mentor and lead junior engineers.

Responsibilities

• Lead end-to-end test plans for generative AI, LLMs, and ML models.
• Validate models for accuracy, drift, latency, robustness and security.
• Build advanced test automation frameworks using Python and PyTest.
• Validate training, validation and test datasets for bias and data integrity.
• Evaluate system scalability and response times under heavy concurrency.
• Mentor junior engineers and collaborate with data scientists and developers.

Skills

Test AI applications

RAG systems

Agents

APIs

Data Pipeline

Education

CS degree or related field

Tools

Python

PyTest

Job description

Role: QA Engineer

Location: Charlotte, NC

Duration: Full time

Primary Skill: Test AI applications, RAG systems, agents, APIs and Data Pipeline using automated development framework

Experience: Minimum 8 years

Roles & Responsibilities

Bachelor's or master's degree in computer science or related field.

Key Responsibilities

• Lead Strategy: Design end-to-end test plans for generative AI, LLMs, and machine learning models.
• Model Validation: Test models for accuracy, drift, latency, robustness, and security vulnerabilities.
• Automation: Build advanced test automation frameworks using Python, PyTest, and specialized AI testing tools.
• Data Quality: Validate training, validation, and test datasets for bias, leakage, and data integrity.
• Performance Testing: Evaluate system scalability and response times under heavy concurrent loads.
• Team Leadership: Mentor junior engineers and collaborate with data scientists and software developers.

Certifications in Automation