Senior AI QA Platform Engineer

Senior AI QA Platform Engineer – Agentic QA Orchestration (Amazon Bedrock)

Company: BONbLOC Technologies

Location: Remote (Candidates must reside in or around Chicago Area, Midwest, New Jersey, or New York)

Role Type: Full-Time / Contract

Seniority Level: Senior Level (7+ Years Experience)

Position Summary

We are seeking a Senior AI QA Platform Engineer to 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. The ideal candidate combines expertise in software engineering, cloud-native platforms, AI/LLM integration, CI/CD automation, and quality engineering.

Primary Responsibilities

• Agentic AI Orchestration: Design and implement AI-powered QA orchestration workflows using Amazon Bedrock, AgentCore, and Multi-Agent Architectures.
• Autonomous QA Capabilities: Develop agent-based automation capabilities for test generation, self-healing test maintenance, failure classification, defect routing, and test intelligence/analytics.
• Framework & Repository Management: Integrate AI workflows with Playwright frameworks and build automated GitHub branch creation, pull request generation, and repository-aware test generation patterns.
• CI/CD & Quality Gates: Design and implement integrations with AWS CodeBuild and enterprise CI/CD pipelines, incorporating rule-based quality gates and AI-assisted failure analysis.
• Enterprise Platform Integrations: Build integrations with Databricks, Jira, qTest, and GitHub, leveraging Databricks Test Data Management (TDM) and analytics for historical context and failure classification.
• AI Governance & Observability: Design and implement AI governance controls including prompt version control, Model Context Protocol (MCP), approved action policies, audit logging, human-in-the-loop workflows, and AI action traceability.
• Cross-Functional Collaboration: Partner with QA, DevOps, Cloud Engineering, Data Engineering, and Security teams to establish enterprise AI testing standards and platform architecture.

Required Technical Skills

• AI & Agentic Systems: Claude, Prompt Engineering, Agentic AI Workflows, Multi-Agent Architectures, Model Context Protocol (MCP).
• Preferred Agent Frameworks: Strands Agents, Amazon Bedrock, AgentCore.
• Programming & Scripting: TypeScript, Node.js, JavaScript, SQL, REST API Development.
• Cloud & AWS: AWS Services (IAM, CodeBuild, CloudWatch, S3, Secrets Manager, Parameter Store).
• DevOps & CI/CD: GitHub, GitHub Actions, CI/CD Pipelines, Infrastructure as Code (Terraform preferred).
• Automation & Enterprise Tools: Playwright, API Testing, Test Automation Framework Architecture, Test Data Management Concepts, Jira, qTest, Databricks.

Preferred Qualifications

• Experience: 7+ years of software engineering, automation engineering, platform engineering, or cloud engineering experience, with 5+ years designing and implementing enterprise test automation solutions.
• AI & Cloud Mastery: Experience building cloud-native solutions on AWS and integrating AI/LLM capabilities into engineering or developer automation platforms.
• Governance & Analytics: Track record of designing governance, auditability, compliance, and operational controls, as well as working with Databricks, TDM, or analytics-driven automation solutions.
• Location Requirements: Candidates must reside in or around the Chicago Area, Midwest, New Jersey, or New York regions.
• Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience.

Preferred Certifications

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

Pay: $90,000.00 - $100,000.00 per year

Work Location: Remote