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Lead the implementation of AI-driven testing strategies, create documentation for GenAI adoption in QA, prototype testing tools, and measure impact across multiple projects while enabling QA teams.

As a GenAI QA Architect, you'll define testing strategies for AI features, design LLM-specific test plans, and enable teams to implement AI in QA processes. You'll prototype tools, integrate LLM testing with CI/CD, and facilitate workshops to share best practices while tracking the impact on QA across projects.

The Project Coordinator will support daily project operations, coordinate teams across locations, manage documentation, budgeting, and stakeholder communication while identifying risks and ensuring satisfaction.

Develop and maintain automated test suites for UI and API testing. Integrate testing into CI/CD, optimize coverage, and collaborate with teams.

Develop automated test suites for UI and API testing, integrate automation into CI/CD pipelines, maintain test frameworks, and collaborate with teams.

Lead the integration of GenAI into QA processes by designing testing strategies, enabling teams, and refining tools for LLM outputs across multiple projects.

Design, develop, and maintain backend services with .NET and C#. Build secure APIs, optimize applications for performance, and collaborate with teams for feature delivery.

Design and maintain scalable backend services using .NET and C#. Build secure APIs, optimize database access, and collaborate on architecture decisions.

The Lead AI Engineer will develop and optimize AI workflows using large language models, collaborate on project objectives, and ensure seamless integration of AI technologies across the project lifecycle.

The Lead AI Engineer role requires overseeing AI project lifecycles, optimizing AI workflows using LLMs, and collaborating with cross-functional teams to align AI solutions with business objectives.