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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing AI-powered quality processes and automation frameworks, leveraging AI tools and large language models to enhance software quality. Proficient in data-driven analysis and quality improvement initiatives, with strong communication skills for collaboration across global teams.
Highest-signal resume keywords
AI Tools ProficiencyLarge Language Models (LLMs)Automation WorkflowsAgile/DevOps MethodologiesData Visualization
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software DevelopmentQuality Assurance (QA)AI-Assisted DevelopmentPrompt EngineeringNetworking ProtocolsBI ToolsData AnalysisQuality Process ImprovementIncident PredictionRoot Cause Analysis
Soft Skills
Interpersonal SkillsCommunication SkillsCreative ThinkingOrganizational SkillsIndependent Work
Tools & Technologies
ClaudeWeb-Building ToolsAutomated Reporting PipelinesSmart DashboardsQuality Tracking Tools
Industry Keywords
Software QualityQuality TargetsData-Driven KPIsQuality Process DocumentationEngineering Teams
About the role
Key responsibilities & impact- Design and implement AI-powered quality processes and automation frameworks that go beyond traditional QA methods.
- Build and maintain automations to streamline quality tracking, reporting, and alerting, including smart dashboards and automated reporting pipelines.
- Leverage AI tools and large language models (LLMs) to accelerate root cause analysis, anomaly detection, and incident prediction.
- Track and analyze customer quality incidents, applying AI-assisted techniques to identify patterns, resolve issues faster, and prevent reoccurrence.
- Assist in driving software quality from concept to release delivery using data-driven KPIs and quality targets.
- Explore and introduce emerging AI methodologies to improve the quality mindset across engineering teams.
- Contribute to quality process improvement initiatives and help maintain quality process documentation and records.
- Collaborate with NVIDIA worldwide support teams, internal engineering and production groups, hardware teams, and Program Management groups.
Requirements
What you’ll need- B.Sc. in Computer Science, Software Engineering, or another relevant technical degree.
- 2+ years of experience in software development, QA, or SW quality roles.
- Hands-on experience with AI tools, LLMs, and automation workflows — especially Claude, web-building tools, and AI-assisted development environments.
- Demonstrated ability to think creatively, challenge existing processes, and push things forward independently.
- Outstanding interpersonal and communication skills — comfortable working with global teams and presenting ideas clearly across levels.
- Strong analytical mindset with the ability to translate data into actionable quality insights.
- Organized, independent, and able to juggle multiple workstreams.
- Fluent English — written and spoken.
- Proven track record of using AI to automate or improve a quality or engineering process.
- Experience building AI-assisted workflows, prompt engineering, or integrating LLM APIs.
- Familiarity with Networking protocols and technologies.
- Experience with Agile/DevOps methodologies.
- Proficiency with BI tools and data visualization.