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Test Engineer Qa Jobs in Atlanta, GA (NOW HIRING)

Key Responsibilities Test Automation Development * Design, develop, and maintain automated test ... Experience mentoring junior QA engineers What You'll Work With: Languages: Python, SQL, JavaScript ...

Key Responsibilities Test Automation Development * Design, develop, and maintain automated test ... Experience mentoring junior QA engineers What You'll Work With: Languages: Python, SQL, JavaScript ...

QA Engineer

Atlanta, GA

$120K - $140K/yr

We are seeking a QA Engineer to lead quality assurance across our software products and help ensure ... This person will own test strategy, strengthen testing processes, improve defect visibility, and ...

Key ResponsibilitiesTest Automation DevelopmentDesign, develop, and maintain automated test ... QA best practices and quality metrics for AI productsCollaborate with developers to identify ...

Work is a company focused on software quality assurance, and they are seeking a Quality Assurance Engineer to ensure software quality through designing, developing, and executing tests. The role ...

Job ID: (790543) Jr. QA Consultant Location: Atlanta, GA Duration: 12+ Months Client: GDOT Hybrid ... Certified Test Engineer (CSTE) * Certified Software Quality Analyst (CSQA) * Certified Manager of ...

All onsite Role: QA Engineer - Must understand Salesforce and Manual Testing!!! We are looking for ... Job Responsibilities: • Create test case artifacts, and perform test execution following standard ...

But wait - we want QA engineers who have more than one dimension to bring to our team. Fly ... RESPONSIBILITIES Develop test plans, test cases, test scripts and test reports on multiple projects ...

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Test Engineer Qa information

See Atlanta, GA salary details

$10

$49

$70

How much do test engineer qa jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for test engineer qa in Atlanta, GA is $49.48, according to ZipRecruiter salary data. Most workers in this role earn between $40.43 and $56.39 per hour, depending on experience, location, and employer.

What is a test engineer QA?

Test Engineer QA (Quality Assurance) professionals are responsible for ensuring the quality and functionality of software applications through systematic testing. They design, develop, and execute test plans and scripts to identify bugs or issues before the software is released. Test Engineers work closely with developers and other stakeholders to understand requirements, report defects, and verify fixes. Their main goal is to deliver high-quality, reliable products to end-users by minimizing errors and improving performance.

How does a test engineer QA typically collaborate with software development and product teams during a project lifecycle?

Test Engineer QAs work closely with software developers and product managers throughout the software development lifecycle. They participate in sprint planning meetings to understand new features, clarify requirements, and identify potential risks early on. Regular communication with developers helps resolve bugs efficiently, while collaboration with product teams ensures test cases align with user expectations and business goals. This cross-functional teamwork is essential for delivering high-quality software and fostering a culture of continuous improvement.

What is the difference between Test Engineer Qa vs Test Analyst?

AspectTest Engineer QaTest Analyst
CertificationsISTQB, CSTEISTQB, CSTE
Work EnvironmentDevelopment teams, QA labsBusiness units, QA teams
Primary FocusDesign, develop, execute tests, automationTest planning, requirements analysis, manual testing
Industry UsageSoftware, hardware, tech companiesSoftware, finance, healthcare sectors

Test Engineer Qa typically focuses on creating and executing automated and manual tests, often working closely with development teams. Test Analysts mainly handle test planning, manual testing, and analyzing requirements. Both roles require similar certifications and are vital in ensuring product quality, but their daily tasks and focus areas differ.

What are the key skills and qualifications needed to thrive as a test engineer QA, and why are they important?

To thrive as a Test Engineer QA, you need a solid understanding of software testing methodologies, test planning, and quality assurance principles, typically supported by a degree in computer science or a related field. Familiarity with automated testing tools (like Selenium, JUnit, or TestNG), bug tracking systems, and possibly ISTQB certification is often expected. Attention to detail, analytical thinking, and strong communication skills help distinguish top performers in this role. These abilities ensure that software products meet quality standards, function as intended, and provide a reliable user experience.

Are QA engineers paid well?

QA engineers typically earn competitive salaries that vary based on experience, location, and industry. Entry-level positions may start lower, but with skills in automation tools and certifications, salaries can increase significantly, especially in tech hubs or specialized testing roles.
Infographic showing various Test Engineer Qa job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, 5% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $102,911 per year, or $49.5 per hour.

Sr. QA Test Engineer

Accord Technologies Inc.

Alpharetta, GA • On-site

$40.25 - $55/hr

Contractor

Re-posted 11 days ago


Job description

Title: QA Test Engineer
Location: Alpharetta, GA
Duration: 7 months
Position type: W2 contract.

Face to Face interview is needed for this position.
 

PS: Qualified QA Test Engineer candidates located near Alpharetta GA to be considered due to the position requiring an onsite presence.
Required Skills, Experience, & Abilities:
- 3+ years in QA automation or SDET-type work (adjust by level); 1+ year exposure to AI/LLM or ML-driven features is a plus. 
- Strong test automation in Python and/or Java/TypeScript. 
- We are a platform team, testing APIs for high performance, automation will be primary focus. 
- Strong communication and analytical skills. 
Additional skills required: 
- Hands-on with frameworks/tools such as: UI: Playwright / Cypress / Selenium and API: pytest + requests, Postman/Newman, REST Assured 
- CI/CD integration: Git, GitHub Actions/Jenkins/GitLab CI, test reporting, gating. 
- Test design: equivalence partitioning, boundary testing, risk-based testing, defect triage. AI-Specific Testing Competencies (Key) 
- LLM/application behavior testing: validating correctness when outputs are probabilistic. 
- Evaluation strategies: golden datasets, scoring rubrics, human-in-the-loop reviews. 
- Non-determinism handling: statistical assertions, repeated runs, variance thresholds. 
- Prompt and regression management: versioning prompts, detecting prompt drift, replay tests. 
- RAG testing (if applicable): retrieval quality (recall/precision), grounding checks, citation validation, doc freshness. 
- Safety & quality checks: hallucination detection, toxicity/PII leakage checks, policy compliance tests. 
Data & Observability:
- Ability to create and maintain test datasets (structured + unstructured), including edge cases. 
- Familiarity with telemetry for AI systems: - logging prompts/outputs safely, traceability, correlation IDs - tools like OpenTelemetry, ELK/Splunk, Datadog/Grafana (any equivalent) 
- Understanding of data privacy constraints (masking/redaction) and secure test data practices. 
- API / Microservices / Cloud 
- Comfortable testing distributed systems: microservices, async workflows, queues/events. 
- Basic cloud proficiency (AWS/Azure/GCP) and containerization (Docker, optional Kubernetes). Performance & Reliability Testing (AI-Aware) 
- Load/performance testing for inference endpoints (latency, throughput, concurrency). 
- Cost-aware testing (token usage, rate limits, fallbacks). 
- Resilience tests: retries, circuit breakers, model timeouts, degraded-mode behavior. 
Nice-to-Have:
Domain Knowledge:
- Familiarity with NLP concepts (embeddings, context windows, temperature/top-p). 
- Experience with AI tooling: LangChain/LlamaIndex, evaluation tools, model gateways. 
- Knowledge of regulatory/security needs relevant to the telecom domain. 
Soft Skills / Ways of Working:
- Strong communication
—able to explain AI quality issues clearly to product and engineering. 
- Comfortable partnering with data science/ML engineers and backend teams. 
- Ownership mindset: building reusable test harnesses, improving quality metrics, preventing regressions.

Education: 
- Bachelor’s in Computer Science, Engineering, Data/Information Systems, or equivalent practical experience.