The QA AI Engineer is responsible for ensuring the quality, reliability, and safety of AI-driven products and proprietary LLM infrastructure. This role involves creating test plans, executing automated and manual test cases, and building evaluation frameworks to validate AI outputs and software behavior.
The Quality Assurance Engineer is responsible for creating and executing comprehensive test plans, including manual, automated, and performance testing. They collaborate with developers and product managers to identify defects and implement effective solutions.
Lead the design and delivery of registry software for environmental commodities, managing the product lifecycle from conceptualization to go-live. Collaborate with cross-functional technical and commercial teams to define priorities, specifications, and success metrics.
Develop, create, and modify computer applications software while implementing secure and scalable architectures. Manage cross-platform database administration and build robust pipelines for infrastructure and application delivery.
The Product Manager will plan and execute initiatives for registry clients, involving business development, scope facilitation, product specifications, and overall delivery to market. This includes leading the engineering effort from inception through go-live and establishing success metrics for initiatives.
