QA Automation Engineer (Gen AI experience) - W2 Only

Saransh Inc; Jersey City (NJ); On-site; USD 90,000 - 120,000; Full time

Job summary

Saransh Inc. in Jersey City is seeking a QA Engineer with Gen AI experience to lead QA efforts on large-scale enterprise applications. You will mentor teams, define test strategy, and own automation initiatives across multiple projects.

You will perform functional and automation testing for capital markets, develop automation frameworks in Java or Python, validate data with SQL, and leverage GenAI tools to boost testing efficiency and quality.

Qualifications

• Lead and mentor QA teams delivering quality engineering for large-scale applications.
• Define test strategy, execution, resource planning, and continuous quality improvements.
• Develop and maintain automation frameworks using Java or Python.
• Validate data using SQL, databases, ETL pipelines, and data services.
• Demonstrate AI fluency by leveraging GenAI tools to improve QE productivity.
• Experience testing high-volume, low-latency financial data platforms is preferred.

Responsibilities

• Lead QA teams and drive test strategy and planning.
• Oversee functional and automation testing across multiple projects.
• Mentor QA engineers and coordinate resource planning.
• Collaborate with cross-functional stakeholders in Agile delivery.
• Ensure data quality and integrity in capital markets applications.

Skills

QA testing

Automation

GenAI

Agile

Leadership

Tools

Java

Python

SQL

Job description

Role: QA Engineer with Gen AI Expereince

Location: NYC, NY, Jersey City, NJ

W2 Position

Job Description

Lead and mentor QA teams delivering quality engineering for large-scale, enterprise-grade applications, driving test strategy, execution, resource planning, and continuous quality improvements across multiple projects.

• Perform functional and automation testing for Capital Markets ensuring quality, reliability, and performance.
• Understanding of index methodologies, benchmark indices, and capital markets data, experience in validating index calculations, market data, reference data, and benchmark-related financial applications or similar capital markets platforms
• Develop and maintain automation frameworks using Java or Python, and execute regression, API, and end-to-end testing.
• Validate data using SQL, databases, ETL pipelines, and Data Services to ensure data accuracy and integrity.
• Demonstrate AI fluency by leveraging AI-powered tools and GenAI assistants to improve test design, test automation, defect analysis, root cause investigation, and overall QE productivity.
• Work with market data, pricing, reference data, index calculation, or similar financial applications.
• Experience testing high-volume, low-latency, real-time data platforms in Financial Services is highly preferred
• Partner with cross-functional stakeholders to define QA strategy, implement Agile delivery practices, manage project risks and dependencies, and successfully deliver complex, large-scale initiatives with high quality and predictable outcomes.