1Kosmos

QA Engineer

• Lead and scale the QA team, including recruitment, mentoring, and performance management.
• Define and implement the overall QA strategy, encompassing functional, regression, performance, and security testing.
• Establish and enforce quality standards, test plans, and best practices across all projects.
• Drive test automation strategy to increase efficiency and reduce manual testing overhead.
• Partner with Engineering and DevOps to integrate automated tests into CI/CD pipelines.
• Monitor and report on key quality metrics (defect density, test coverage, release stability).
• Collaborate with Product and Engineering to ensure requirements are testable and aligned with customer expectations.
• Ensure adherence to compliance frameworks (e.g., SOC 2, ISO 27001, GDPR) as applicable.
• Manage QA tools, infrastructure, and budget for testing environments.
• Serve as the voice of quality in release readiness reviews and executive meetings.
• Embed quality into every stage of the development lifecycle and define metrics to improve release confidence, reduce defects, and accelerate time-to-market.

Director of Quality Assurance

Marketing Operations

• Build and manage ABM workflows using modern GTM automation tools and HubSpot CRM
• Collaborate with sales and marketing to define ICPs and enrich/segment target accounts
• Launch and iterate personalized outbound campaigns including messaging, sequencing, and delivery timing
• Use AI tools to generate and personalize outbound content
• Analyze campaign performance metrics (reply rates, open rates, conversion rates) and suggest optimizations
• Maintain data hygiene and ensure CRM records are enriched, accurate, and actionable
• Partner cross-functionally with content, product marketing, and sales to align messaging and outreach
• Research and test new tools or workflows to scale account-based prospecting and engagement
• Own programs and build systems from Day 1 with visibility to senior leaders

Marketing Operations Coordinator

Machine Learning Engineer

• Design and implement AI models for image classification, object detection, OCR, and feature extraction.
• Develop real-time image quality assessment and capture guidance algorithms.
• Create and maintain data pipelines for collecting, cleaning, augmenting, and labeling datasets.
• Implement model optimization techniques for mobile (on-device) and cloud inference.
• Apply fraud detection methods to identify tampering, forgeries, or replay attacks in visual data.
• Integrate ML models into production-grade APIs and mobile SDKs.
• Monitor, evaluate, and continuously improve model accuracy and performance.
• Collaborate with product and engineering teams to align AI capabilities with business goals.
• Own the full ML lifecycle from dataset creation and model training to deployment and performance optimization.

Director of Quality Assurance

Marketing Operations Coordinator

AI / Machine Learning Engineer