Job Summary

We are seeking a seasoned QE Strategist and AI Automation Architect to join our Quality Engineering & Automation practice. This is a highly visible, client-facing leadership role that sits at the intersection of AI innovation, enterprise test strategy, and delivery excellence. The ideal candidate brings deep insurance industry expertise, a strong hands-on technical foundation in AI-driven test automation, performance testing, and a proven track record of leading geographically distributed QE teams.

Responsibilities

- Strategic Leadership & QE Governance: Define and own the enterprise-wide testing strategy, including standards, methodologies, governance models, and quality frameworks.
- Strategic Leadership & QE Governance: Conduct current-state assessments of client systems, processes, and tooling; provide actionable, data-driven quality recommendations.
- Strategic Leadership & QE Governance: Lead the design and implementation of Agentic AI testing frameworks and drive the organizations overall AI QE strategy.
- Strategic Leadership & QE Governance: Serve as a thought leader on AI-infused quality engineering, continuously evaluating emerging tools and incorporating them into the automation roadmap.
- Client Engagement & Business Development: Contribute substantively to RFPs, proposal development, and client presentations; effectively articulate complex technical concepts to C-suite executives and non-technical stakeholders.
- Client Engagement & Business Development: Build and sustain trusted advisor relationships with client leadership, proactively identifying opportunities to expand QE value delivery.
- Client Engagement & Business Development: Represent the QE practice in steering committees, executive reviews, and cross-functional planning sessions.
- Client Engagement & Business Development: Contribute to creation of GTM assets & reusable accelerators creation, write thought leadership articles/blogs/webinars, speak in conferences or panels.
- Delivery & Program Management: Own end-to-end delivery accountability for client engagements managing multiple mid-to-large teams across geographies and time zones.
- Delivery & Program Management: Develop project plans, resource models, risk registers, and status reporting for concurrent QE workstreams.
- Delivery & Program Management: Partner with development, DevOps,



and QA teams to ensure seamless integration of AI test automation into CI/CD pipelines and Agile delivery cycles.
- Architecture & Hands-On Engineering: Design and architect robust, scalable, and maintainable test automation frameworks covering functional, regression, performance, and integration testing.
- Architecture & Hands-On Engineering: Be hands-on in building frameworks and scripts centered on AI, automation & performance, including the creation of AI agents from scratch.
- Architecture & Hands-On Engineering: Create POCs around AI & automation and conduct technical demos for clients.
- Architecture & Hands-On Engineering: Establish and enforce coding standards, best practices, and code review processes for automated and performance test scripts.
- Architecture & Hands-On Engineering: Evaluate, select, and integrate best-fit automation tools and technologies aligned to project and organizational needs.
- Architecture & Hands-On Engineering: Develop automated monitoring and reporting mechanisms to track test execution, defect trends, and quality metrics; provide stakeholders with regular health reports.
- People Leadership & Capability Development: Mentor and develop QE engineers and leads, elevating technical skills and deepening understanding of AI-infused automation and performance testing.
- People Leadership & Capability Development: Foster a continuous-improvement culture through knowledge sharing, structured training programs, and adoption of industry best practices.
- People Leadership & Capability Development: Provide technical leadership and subject-matter expertise across test automation teams and cross-functional stakeholders.

What you'll do

- Define and drive enterprise-wide Quality Engineering and test automation strategies.
- Architect and implement AI-powered testing frameworks, automation solutions, and Agentic AI initiatives.
- Lead quality assessments, governance programs, and transformation roadmaps for clients.




- Partner with stakeholders and executive leadership to deliver scalable, high-quality solutions.
- Oversee end-to-end delivery of complex QE programs across global teams.
- Integrate automation and performance testing into Agile and CI/CD pipelines.
- Build POCs, conduct client demonstrations, and contribute to thought leadership initiatives.
- Mentor teams and establish best practices for quality engineering, automation, and performance testing.

What you'll bring

- 14+ years of experience in software testing, quality engineering, and test automation.
- Proven experience leading large-scale QE programs and distributed technical teams.
- Deep expertise in AI-driven test automation, test architecture, and quality governance.
- Robust hands-on experience with automation frameworks, performance testing, and CI/CD integration.
- Experience engaging with executive stakeholders and managing client relationships.
- Domain expertise within the insurance industry (P&C;, Life, Health, or Annuities).
- Strong leadership, communication, problem-solving, and strategic thinking skills.

AI Fluency Expected

At Myridius, we expect AI fluency across all roles. This means the ability to effectively and responsibly use AI-enabled tools to improve productivity, quality, analysis, decision-making, documentation, testing, delivery, and problem-solving within ones function. All candidates should be comfortable working with AI as a day-to-day enabler while applying sound judgment, critical thinking, and accountability for outcomes.

Good to Have

- Experience designing and implementing Agentic AI solutions and AI-powered testing frameworks.
- Certifications such as ISTQB Advanced, PMP, CSM, or equivalent quality and project management credentials.
- Experience contributing to RFPs, proposals, GTM assets, and thought leadership initiatives.
- Knowledge of modern DevOps, cloud platforms, and enterprise quality engineering tools.
- Experience speaking at industry conferences, webinars, or technology forums.
- Advanced degree in Computer Science, Engineering, or a related technical discipline.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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