Quality Manager

Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.

Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.

Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.

Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.

As a company redefining operations through AI innovation, our ability to deliver consistently high-quality outcomes is at the core of the value we provide to our clients. We are seeking a detail-oriented and impact-driven Delivery Quality Manager to ensure that our AI training and multilingual data operations maintain the highest standards of accuracy, consistency, cultural relevance, and linguistic excellence.

In this role, you will work in close collaboration with some of the most influential organizations in generative AI and LLM development. You’ll act as a quality guardian across our enterprise delivery programs—ensuring that our human-in-the-loop (HITL) workflows, advanced multilingual data generation processes, and high-touch client services operate at peak precision and reliability.

You’ll partner with Operations Managers, project leads, and client stakeholders to define and implement robust quality assurance protocols, drive performance improvements, and cultivate a culture of continuous enhancement across delivery teams. From proactive QA audits to root-cause analyses, you’ll play a mission-critical role in maintaining the trust and satisfaction of some of the world’s most forward-thinking AI labs and companies.

This position requires an analytical mindset, a sharp eye for detail, and a passion for operational excellence. Success in this role means not only identifying problems—but creating scalable systems and frameworks to prevent them. You’ll be on the front lines of building the standards that shape how human-generated data trains and improves the AI models of tomorrow.

• Cross-Functional Collaboration:
  
  Work closely with Delivery, Product, Engineering, and Customer Success teams to address quality concerns and build preventive measures.
• Process Optimization:
  Identify process inefficiencies or gaps in both AI data and multilingual pipelines, and work with relevant teams to streamline operations and improve delivery accuracy and speed.
• Reporting & Insights:
  Generate regular reports and insights on delivery performance trends, multilingual QA activities, and recommendations to leadership.
• Quality Assurance Strategy:
  Develop and implement comprehensive QA frameworks for large-scale AI data and multilingual delivery workflows, aligned with industry best practices and internal standards.
• Tooling & Automation:
  Evaluate and implement QA tools and automation frameworks to streamline quality checks and reduce manual errors across delivery pipelines.

• Bachelor's degree in Operations Management, Engineering, Computer Science, Linguistics, or related field.
• Proven expertise in language QA concepts and workflows, including linguistic quality assessment, cultural adaptation, and managing multilingual projects.
• 5+ years of experience in quality assurance, service delivery, or operations, preferably in a tech, localization or AI-focused environment.
• Deep understanding of delivery and multilingual life cycles, QA methodologies, and performance metrics.
• Experience working in agile environments and using project management tools
• Strong analytical skills with experience in data-driven…