QA Automation Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Princeton (NJ); Presencial; USD 86.000 - 123.000; Jornada completa

Descripción de la vacante

MACHINE LEARNING TECHNOLOGIES LLC is seeking a hands-on QA Automation Engineer for an 8-month engagement in Princeton, NJ. You will own the AWS-hosted regression framework and drive improvements across UI, API, and service layers, implementing robust tests and infrastructure fixes.

The ideal candidate has 8+ years of QA experience, strong Java, Selenium, Cucumber/BDD, and deep AWS testing expertise, with a track record of reducing regression runtime and flakiness while collaborating with DevOps

Formación

• 8+ years of QA experience across functional and automation.
• Proficient in Java; able to write and debug framework code.
• Experience building and improving automation frameworks in AWS.

Responsabilidades

• Design and execute functional test cases; validate data via SQL.
• Build, extend and refactor the core automation framework (UI, API, service layers).
• Own the AWS automation framework; fix cloud failure modes rather than masking.
• Harden environment provisioning, seeding, teardown and secrets management.
• Improve end-to-end AWS regression process; reduce runtime via parallelisation.
• Analyze logs and stack traces to isolate root causes.
• Integrate suites in CI/CD; collaborate with DevOps and Development.

Conocimientos

QA experience

Strong Java

Selenium

Cucumber/BDD

SQL

AWS debugging

Jenkins/CI-CD

Git

Herramientas

AWS (EC2/ECS)

S3

SQS

RDS

CloudWatch

IAM

Descripción del empleo

Job Overview

• Job ID: J54441
• Job Title: QA Automation Engineer
• Location: Princeton, NJ
• Duration: 8 Months + Extension
• Domain Exposure: Insurance
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C
• Work Authorization: US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
• Bill Rate: $76/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 Hands-on QA Engineer covering both functional testing and automation, with ownership of the AWS-hosted regression framework and process — engineering fixes at framework and infrastructure level, not just running tests and analysing results. Key Responsibilities

• Design and execute functional test cases; validate data directly via SQL.
• Build, extend and refactor the core automation framework (UI, API and service layers).
• Own the AWS automation framework — permanently fix cloud failure modes (container restarts, load balancer timeouts, DB connectivity and connection‑pool exhaustion, S3/SQS integration, IAM/credential expiry, config drift) rather than re‑running or masking them.
• Harden environment provisioning, seeding, teardown and secrets management so runs start from a known‑good baseline.
• Implement resilience in the framework — retry with backoff, health checks and readiness gates, graceful handling of transient cloud failures.
• Improve the end‑to‑end AWS regression process — reduce runtime via parallelisation and sharding, drive down flaky tests against measurable targets, and add failure trend dashboards and automatic artefact capture.
• Analyse logs and stack traces to isolate root cause; classify failures as product defect, script defect, test data, environment or timing.
• Integrate and maintain suites in CI/CD; partner with DevOps and Development to clear infrastructure blockers and communicate risk.

Required Skills

• 8+ years QA across functional and automation.
• Strong Java — able to write and debug framework code, not just scripts.
• Selenium, Cucumber/BDD, solid SQL.
• Proven experience debugging, fixing and improving automation frameworks in AWS (EC2/ECS, S3, SQS, RDS, CloudWatch, IAM).
• Track record of measurably reducing regression runtime and flakiness.
• Jenkins/CI-CD, Maven, Git.
• Strong analytical mindset; able to work independently through intermittent, ambiguous failures.

Equal Opportunity Employer 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.