lilt-corporate - Director of Quality
Requirements
• Agent design and build: demonstrable, hands-on experience designing, building and running LLM-based agents in production. Please be ready to walk us through agents you have built. • Data-driven quality management: scripting or data skills (e.g. Python, SQL), with experience turning quality data into actionable metrics, preventive controls and measurable improvements. • LLM model improvement: proven experience improving LLM output quality. • Significant experience running quality systems, including leading audits (internal and external), compliance programmes, and writing and maintaining processes and procedures. Quality certifications such as Six Sigma are a plus. • Experience leading structured CI (RCA, CAPA, KPI reviews). • Experience managing and developing people. • Customer advisory and cross-functional partnership: a clear communicator who can translate customer quality requirements into acceptance criteria and governance, advise on quality, cost and speed trade-offs, and work credibly with customers, executives and technical teams. • Background in localisation, translation or language services. • Experience in customer-facing quality roles for enterprise accounts. • Research and Product collaboration: a track record of working with research scientists and product managers to turn quality insight into product requirements and shipped improvements. • Our founders, Spence and John met at Google working on Google Translate. As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. While together at Google, they were amazed to learn that Google Translate wasn’t used for enterprise products and services inside the company.The quality just wasn’t there. So they set out to build something better. LILT was born. • LILT has been a machine learning company since its founding in 2015. At the time, machine translation didn’t meet the quality standard for enterprise translations, so LILT assembled a cutting-edge research team tasked with closing that gap. While meeting customer demand for translation services, LILT has prioritized investments in Large Language Models, human-in-the-loop systems, and now agentic AI. • With AI innovation accelerating and enterprise demand growing, the next phase of LILT’s journey is just beginning. • What sets our platform apart: • Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent • Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing • 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation • Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review • LILT IN THE NEWS • Featured in The Software Report’s https://www.thesoftwarereport.com/the-top-100-software-companies-of-2024/ Top 100 Software Companies! • LILT makes it onto the Inc. 5000 List https://labs.lilt.com/lilt-listed-on-the-2024-inc-5000. • LILT’s continues to be an intellectual powerhouse, holding numerous patents https://patents.justia.com/inventor/john-sturdy-denero that help power the most efficient and sophisticated AI and language models in the industry. • Check out all our news on our website https://lilt.com/news. • Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy. • At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at [email protected].
Responsibilities
• Quality Agent leadership • Evaluate, design and build reliable Quality Agents with well-defined tools and clear, structured instructions. • Use orchestration patterns to evolve from a single agent to multi-agent systems. • Define evaluation criteria, test sets and success metrics for agent performance, and run agents in production with clear monitoring and escalation paths. • Drive adoption across teams and show measurable reductions in manual quality effort. • Research and Product partnership • Work closely with Research and Product on ADQ, LLM model improvements, AI Review, AI QA, and new and emerging AI workflows. • Turn quality findings into product requirements, evaluation criteria and continuous feedback loops that improve model and workflow output. • Act as the voice of quality in roadmap discussions, and help decide where human review, AI review or both are needed. • Audit, compliance and procedure • Own LILT's approach to internal and external audits, including ISO certification (e.g. ISO 17100, ISO 18587, ISO 9001) and customer audits. • Plan and run periodic internal audits, manage evidence collection, and track corrective and preventive actions to closure. • Standardise and maintain SOPs, workflows and quality documentation, and keep them current as AI workflows change how we work. • Make sure quality processes meet customer, contractual and regulatory requirements. • Customer advisory • Partner with Customer Success and Delivery to define proactive quality programmes, success metrics and governance for strategic accounts, including AI-forward enterprise and life science / regulatory programmes. • Translate customer quality requirements into clear pre-delivery acceptance criteria, validation methods and risk-appropriate controls. • Advise customers on the right quality, cost and speed mix and where automated, agent-verified, human-verified or combined workflows are appropriate. • Represent LILT's quality function as a credible subject-matter authority in customer business reviews, audits and escalations, using quality data and metrics to demonstrate fitness for purpose. • Continuous improvement • Lead structured CI across the Commercial business: root cause analysis, corrective and preventive actions, KPI reviews and retrospectives. • Own a proactive quality metrics framework that makes errors, PQs, rework and trends visible, and use it to prioritise improvements and demonstrate outcomes. • Strengthen quality controls across review, delivery and follow-through, including mandatory account-specific checks, intervention on critical findings and clear escalation ownership. • Partner with Product and Engineering to automate checks and escalation, and verify that corrective actions prevent recurrence rather than ending at rework or ticket closure. • Expert Operations partnership • Partner with Expert Supply and Ops to embed processes, guidance and quality feedback that maintain a high-quality pipeline of experts. • Use quality findings and recurring failure patterns to improve expert qualification, guidance and ongoing quality management. • Team leadership • Lead and develop the Quality team, including the customer-facing Quality Manager and Quality Coordinators. • Establish the team's operating cadence and evolve how the team works as Quality Agents reduce manual coordination work. • Oversee embedded Quality Manager staffing sold as a service to customers, ensuring the role owns the specific quality programmes and initiatives those customers pay for. • Develop playbooks for AI-driven quality management and keep staffing-as-a-service delivery aligned with LILT's quality standards.
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