About WorkSpan
The next era of growth is being driven by business interoperability. Cloud, genAI, solutions combining services and software- more and more, companies outpace their competition not just through building superior products, but by creating stronger partnerships, paths to market, and better business models for winning together. Cloud providers, service providers, tech partners and resellers are teaming up to win more deals together through co-selling.
WorkSpan is building the world’s largest, trusted co-selling network.
WorkSpan already has seven of the world’s ten largest partner ecosystems on our platform and $50B of customer pipeline under active management. AWS, Google, Microsoft, MongoDB, PagerDuty, Databricks and dozens of others trust WorkSpan to accelerate and amplify their ecosystem strategies.
With a $30M series C and backing from world class investors Insight Partners, Mayfield, and M12, WorkSpan is poised to drive the future of B2B. Come be a part of it.
Join our team for the opportunity to:
● Own your results and make a tangible impact on the business
● Develop a deep understanding of GTM working closely with leadership across sales & marketing
● Work with driven, passionate people every day
● Be a part of an ambitious, supportive team on a mission
The Role:
As our Director of Quality Engineering, you will be a key leader in our engineering organization. You will be responsible for building and leading a world-class QA team, while also defining and executing a strategy to leverage AI to revolutionize our development and testing methodologies. This role requires a deep understanding of not just traditional software QA, but also the emerging challenges of validating intelligent, autonomous systems. You will shape the future of quality for a new class of software.
Your Responsibilities:
Team Leadership & Vision
Lead, mentor talented QA engineers, fostering a culture of innovation, collaboration, and continuous improvement. Set a clear vision for how quality is defined and achieved in an AI-driven software development environment.
AI-Driven Quality Strategy
Develop and implement a comprehensive strategy for developing and testing products built leveraging agentic AI and for using GenAI to enhance testing itself. Pioneer and define a new suite of quality and performance metrics for Generative and Agentic AI models, focusing on areas like accuracy, bias, safety, relevance, and autonomous task completion. Design novel testing methodologies to validate the autonomous behavior of Agentic AI systems within our development process, ensuring their reliability and alignment with intended goals.
Cross-Functional Collaboration
Partner closely with product, engineering, DevOPS to embed a "quality-first" mindset in every stage of the development lifecycle for our agentic systems. Act as the key subject matter expert on AI quality, effectively communicating risks, strategies, and results to stakeholders at all levels.
Process & Tooling
Evolve our test automation frameworks to handle the non-deterministic and dynamic nature of AI-driven software. Drive the selection and implementation of new tools and infrastructure required for robustly testing and monitoring AI models and agents in production.
Your Qualifications:
- 15 + years’ experience in software quality engineering
- 7 + years of leading and managing quality teams
- Ability to work autonomously and in a team; should have managed a group of 20+ functional and automation engineers.
- Proven ability to define and implement advanced test strategies, automation frameworks, and developer tooling to facilitate a "shift-left" approach to quality and successfully integrate automation within CI/CD pipelines.
- Exceptional analytical, problem-solving, and communication skills for guiding complex system software, network, and security quality efforts, and effectively aligning expectations with external stakeholders.
- A strong passion for continuous improvement and a demonstrated ability to challenge existing processes to improve testing efficiency and the overall quality of products delivered to market.
- Executive-level communication and stakeholder management skills
- Strong analytical and problem-solving capability with data-driven decision making
- Experience leveraging QA tools, automation, and analytics platforms
