Senior AI QA Platform Engineer

Kforce has a client in Chicago, IL that is seeking a Senior AI QA Platform Engineer. Summary: In this role, the Engineer will design and implement an enterprise AI-enabled QA Orchestration Platform leveraging Amazon Bedrock, AgentCore, Playwright, AWS CodeBuild, GitHub, Databricks, Jira, and qTest. This platform will utilize agentic AI workflows to generate and maintain automated tests, orchestrate execution paths, classify test failures, create actionable defects, and provide governance, observability, traceability, and auditability across the QA lifecycle. expertise in software engineering, cloud-native platforms, AI/LLM integration, CI/CD automation, and quality engineering to help establish a next-generation AI-powered testing ecosystem. Responsibilities:

• Design and implement AI-powered QA orchestration workflows using Amazon Bedrock and AgentCore
• Develop agent-based automation capabilities for: - Test generation - Test maintenance - Failure classification - Defect routing - Test intelligence and analytics
• Integrate AI workflows with Playwright automation frameworks and repository-aware test generation patterns
• Build automated GitHub branch creation, pull request generation, and repository management capabilities
• Design and implement integrations with AWS CodeBuild and enterprise CI/CD pipelines
• Develop rule-based quality gates and AI-assisted failure analysis workflows
• Build integrations with Databricks, Jira, qTest, and GitHub
• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience
• 7+ years of software engineering, automation engineering, platform engineering, or cloud engineering experience
• 5+ years designing and implementing enterprise test automation solutions
• Experience building cloud-native solutions on AWS
• Experience integrating AI/LLM capabilities into engineering or automation platforms
• Experience developing CI/CD pipelines, automation frameworks, and developer platforms
• Experience designing governance, auditability, compliance, and operational controls
• Experience with Databricks, Test Data Management (TDM), or analytics-driven automation solutions
• Experience implementing Infrastructure as Code using Terraform
• Required Technical Skills AI & Agentic Systems: Claude, Prompt Engineering, Agentic AI Workflows, Multi-Agent Architectures, MCP (Model Context Protocol)

• AWS Certified Solutions Architect
• AWS Certified AI Practitioner HashiCorp Terraform Associate
• AWS Certified Developer Associate

• Strands Agents, Amazon Bedrock, AgentCore
• Programming: TypeScript, Node.js, JavaScript, SQL, REST API Development
• Cloud & AWS: AWS, IAM, CodeBuild, CloudWatch, S3, Secrets Manager, Parameter Store
• DevOps & CI/CD: GitHub, GitHub Actions, CI/CD Pipelines, Infrastructure as Code (Terraform preferred)
• Automation: Playwright, API Testing, Test Automation Framework Architecture, Test Data Management Concepts
• Enterprise Platforms: Jira, qTest, Databricks