Responsibilities
Apply AIassisted test generation, test maintenance, and regression optimization using Codex or similar AI coding tools
Maintain test evidence, traceability, and release signoff practices; support release checkpoints and quality metrics
Cross-train and provide QA coverage as needed.
Essential Skills
Job
6-8 years of experience in QA, software testing, or qualityengineering
Experience defining teststrategy, test plans,test scope, and release-readiness criteria
Experience creating and managing feature, regression, smoke, andend-to-end test plansin VersionOne or similar Agile ticketing systems
Experience executing featurevalidation, regression testing, exploratory testing, and UAT support
Experience with risk-based testing, defect triage, and coverage tracking
Experience validating acceptance criteria, documenting defects, and driving retest/closure workflows
Understanding of testevidence, traceability, and release signoffpractices
Working knowledge of SQL fortest data validation, troubleshooting, and basicdatabase queries
Familiarity with job monitoring, pipeline status checks, logs,and environment-level troubleshooting
Ability to validate API responses, payloads, and system workflows at a functional level
Experience operating in Agile delivery models such as Scrum and Kanban
Experience with VersionOne, Jira, or equivalent ticketing systems for defect tracking and sprint support
Understanding of Test Ops concepts, including test execution visibility, release checkpoints, and quality metrics
Personal
Excellent communication and interpersonal skills,with the abilityto coordinate with product, development, and business stakeholders
Strong attention to detail withdisciplined test evidence and traceability practices
A proactive approach to problem solving and release-readiness ownership
Willingness to adoptnew AI-assisted toolsand continuously improveQA practices
PreferredSkills
Job
Exposure to usingCodex or similarAI coding toolsto accelerate automated test creation
Familiarity with AI-assisted test generation, testmaintenance, and regression optimization
Understanding of future-state QA automation approaches such as AI-generated test cases, self-healing automation, and intelligent test selection
Familiarity with Dagsterrun monitoring and data pipeline validation
Experience supporting releasecycles for data-driven or SaaS applications
Personal
Demonstrate proactive thinking
Strong interpersonal relations and stakeholder coordination skills
Ability to workunder stringent deadlines and demanding clientconditions
Other Relevant Information
Bachelor's degree in Computer Science, Information Technology, or a relatedfield
6-8 years of experience in QA or quality engineering, preferably for data-driven or SaaS applications
Willingness to cross-train and provide QA coverage acrossmultiple applications
Skills Required
- 6-8 years of experience in QA, software testing, or quality engineering
- Experience defining test strategy, test plans, test scope, and release-readiness criteria
- Experience creating and managing feature, regression, smoke, and end-to-end test plans in VersionOne or similar Agile ticketing systems
- Experience executing feature validation, regression testing, exploratory testing, and UAT support
- Experience with risk-based testing, defect triage, and coverage tracking
- Experience validating acceptance criteria, documenting defects, and driving retest and closure workflows
- Understanding of test evidence, traceability, and release signoff practices
- Working knowledge of SQL for test data validation, troubleshooting, and basic database queries
- Familiarity with job monitoring, pipeline status checks, logs, and environment-level troubleshooting
- Ability to validate API responses, payloads, and system workflows at a functional level
- Experience operating in Agile delivery models such as Scrum and Kanban
- Experience with VersionOne, Jira, or equivalent ticketing systems for defect tracking and sprint support
- Understanding of Test Ops concepts, including test execution visibility, release checkpoints, and quality metrics
- Bachelor's degree in Computer Science, Information Technology, or a related field
- Exposure to Codex or similar AI coding tools for automated test creation
- Familiarity with AI-assisted test generation, test maintenance, and regression optimization
- Understanding of AI-generated test cases, self-healing automation, and intelligent test selection
- Familiarity with Dagster run monitoring and data pipeline validation
- Experience supporting release cycles for data-driven or SaaS applications
The Hackett Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Hackett Group and has not been reviewed or approved by The Hackett Group.
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Flexible Benefits — Remote/hybrid flexibility is consistently highlighted, with support for home-office expenses in some cases. Feedback suggests location flexibility is a bright spot that improves day-to-day experience.
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Fair & Transparent Compensation — Publicly posted salary ranges and role-specific target bands offer clear expectations and help candidates assess fit. Feedback suggests compensation can be competitive for certain roles and markets.
The Hackett Group Insights
What We Do
The Hackett Group, Inc. (NASDAQ: HCKT) is a Gen AI strategic consulting and executive advisory firm that enables Digital World Class® performance. Using Hackett AI XPLR™ and ZBrain™ – our ideation through implementation platforms – our experienced professionals help organizations realize the power of Gen AI and achieve quantifiable, breakthrough results, allowing us to be key architects of their Gen AI journey. Our expertise is grounded in unparalleled best practices insights from benchmarking the world’s leading businesses – including 97% of the Dow Jones Industrials, 89% of the Fortune 100, 70% of the DAX 40 and 55% of the FTSE 100. Visit us at www.thehackettgroup.com.
