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Develop, test, support, and troubleshoot production software for a scalable TLD Registry Platform. Build web applications, services, background services, and class libraries using object-oriented programming, SQL, NoSQL, and AWS cloud technologies. Participate in the full software development lifecycle, provide on-call support, identify root causes, improve system performance and maintainability, and collaborate with experienced engineers across a global organization.

Develop, test, support, and troubleshoot production software for a TLD registry platform. Collaborate with experienced engineers to build scalable, reliable solutions using cloud technologies, databases, web applications, services, and background systems. Participate throughout the software development lifecycle, provide on-call support, identify root causes, and improve system performance and maintainability while supporting global business operations.

Lead Known’s channel and strategic partnership ecosystem for DNSid, focusing on cloud providers, identity and trust platforms, GSIs, and technology partners. Develop partnership strategy, commercial models, joint go-to-market motions, integrations, and enterprise adoption programs. Lead GSI implementation and Customer Success teams, build executive relationships, establish reference architectures, and convert early deployments into repeatable partner-led growth. The role is a remote U.S. contract-to-hire opportunity.

Build and scale Known’s advisor council, ecosystem partnerships, and stakeholder engagement infrastructure. Manage advisor and partner relationships, coordinate events and community programming, support the Global Agent Accountability Initiative, track referrals and leads, and collaborate with executive, commercial, marketing, communications, CTO, and standards teams. The role requires strong relationship management, technical fluency, discretion, responsiveness, and execution in an ambiguous AI-focused environment.

Manages Business Operations resource allocation, daily workflows, process improvement, operational roadmaps, and cross-functional delivery for registry activities. Leads a global team, oversees hiring and performance management, prioritizes stakeholder requests, monitors KPIs, reviews deliverables, and partners with Product and Engineering on automation, bug fixes, and workflow enhancements.

Manages Business Operations resource allocation, workflows, process improvement, and operational projects for a global registry organization. Leads a distributed team, coordinates with Product, Engineering, Account Management, Technical Support, and Revenue Operations, prioritizes stakeholder requests, tracks KPIs and milestones, improves automation and reporting, and oversees hiring, coaching, and performance management.

Leads global Business Operations for the Identity Digital Registry, overseeing resource allocation, workflow improvement, operational roadmaps, reporting, project coordination, and stakeholder satisfaction. Manages teams across Toronto and Dublin, partners with Product and Engineering on system improvements and automation, and oversees hiring, onboarding, coaching, performance management, KPIs, and capacity planning.

Leads Business Operations by allocating resources, managing global staff, improving workflows, establishing SOPs, overseeing operational projects, and coordinating cross-functional stakeholders. The role drives process automation, reporting, team performance, hiring, coaching, and capacity planning while partnering with Product and Engineering on system improvements and registry operations.

Independently design, build, test, and deliver production features for a scalable TLD registry platform. Develop C#/.NET and Python microservices, implement AWS-based solutions, optimize CI/CD and infrastructure-as-code pipelines, and ensure reliability through unit and integration testing. Collaborate with engineers, troubleshoot complex technical issues, and take ownership of assigned software delivery tasks.

Develops, deploys, and monitors production data and machine learning pipelines. Responsibilities include data preparation, exploratory analysis, predictive modeling, feature and algorithm selection, model deployment, infrastructure development, and monitoring model performance, data quality, drift, latency, and reliability. The role also requires communicating insights, collaborating cross-functionally, and translating business problems into scalable data and ML solutions.