Tabby

Engineer

• Respond to alerts and incidents by triaging, assessing impact, and escalating to the right teams
• Coordinate incident resolution and keep stakeholders informed
• Participate in the on-call rotation, including occasional out-of-hours alerts
• Contribute to post-mortems and follow up on action items
• Handle requests from the support team and colleagues
• Investigate technical issues using logs, metrics, and SQL; identify bugs and create clear development tasks
• Maintain runbooks and documentation for L1 and L2 teams
• Improve support and incident management processes
• Automate routine tasks and contribute to internal tools such as BackOffice and alerting
• Explore and implement AI tools and LLM-based solutions for request handling, incident triage, and documentation

Service Desk Engineer

Engineering Manager

• Own the end-to-end product data pipeline: ingestion from feeds and plugins, ML enrichment, moderation and publication, with clear SLAs for freshness, coverage and quality
• Lead the ML roadmap for catalogue intelligence, including category tree and attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations
• Lead large cross-team projects and drive them to production
• Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation
• Review feature designs and ensure non-functional requirements are met, including ML evaluation, inference cost, latency and data residency
• Build and maintain evaluation and labeling infrastructure to measure model changes before production
• Oversee technical debt management and incident handling across ML and backend services
• Hire, evaluate and motivate team members; grow ML engineers into owners of business outcomes
• Build cross-team collaboration with Shopping, Offers, Monetisation, catalogue operations and partner support
• Foster a results- and business-oriented culture
• Monitor key team performance indicators
• Ensure process and delivery transparency for stakeholders and partner functions
• Optimise processes to improve productivity
• Lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst
• Work closely with Shopping, Offers and Monetisation teams, catalogue operations and partner support

Engineering Manager, ML

• Own the end-to-end product data pipeline: ingestion from feeds and plugins, ML enrichment, moderation and publication, with clear SLAs for freshness, coverage and quality
• Lead the ML roadmap for catalogue intelligence, including category tree and attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations
• Lead large cross-team projects and drive them to production
• Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation
• Review feature designs and ensure non-functional requirements are met, including ML evaluation, inference cost, latency and data residency
• Build and maintain evaluation and labeling infrastructure to measure model changes before production
• Oversee technical debt management and incident handling across ML and backend services
• Hire, evaluate, and motivate team members; develop ML engineers into owners of business outcomes
• Collaborate with Shopping, Offers, Monetisation, catalogue operations and partner support to increase efficiency
• Foster a results- and business-oriented culture
• Monitor key team performance indicators
• Ensure process and delivery transparency for stakeholders and partner functions
• Optimise processes to improve productivity
• Lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst
• Work closely with the Shopping, Offers and Monetisation teams, catalogue operations and partner support

• Own the end-to-end product data pipeline: ingestion from feeds and plugins, ML enrichment, moderation and publication, with clear SLAs for freshness, coverage and quality
• Lead the ML roadmap for catalogue intelligence, including category tree and attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations
• Lead large cross-team projects and drive them to production
• Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation
• Review feature designs and ensure non-functional requirements are met, including ML evaluation, inference cost, latency and data residency
• Build and maintain evaluation and labeling infrastructure to measure model changes before production
• Oversee technical debt management and incident handling across ML and backend services
• Hire, evaluate, and motivate team members; develop ML engineers into owners of business outcomes
• Build cross-team collaboration with Shopping, Offers, Monetisation, catalogue operations and partner support
• Foster a results- and business-oriented culture
• Monitor key team performance indicators
• Ensure process and delivery transparency for stakeholders and partner functions
• Optimise processes to improve productivity
• Lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst
• Work closely with Shopping, Offers and Monetisation teams, catalogue operations and partner support

• Own the end-to-end product data pipeline, including ingestion from feeds and plugins, ML enrichment, moderation and publication
• Lead the ML roadmap for catalogue intelligence, including category trees, attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations
• Lead large cross-team projects and drive them to production
• Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation
• Review feature designs and ensure non-functional requirements for ML evaluation, inference cost, latency and data residency
• Build and maintain evaluation and labeling infrastructure for measuring model changes before production
• Oversee technical debt management and incident handling across ML and backend services
• Hire, evaluate and motivate team members; develop ML engineers into owners of business outcomes
• Collaborate with Shopping, Offers, Monetisation, catalogue operations and partner support
• Foster a results- and business-oriented culture
• Monitor key team performance indicators
• Ensure process and delivery transparency for stakeholders and partner functions
• Optimise processes to improve productivity
• Lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst
• Work with Shopping, Offers and Monetisation teams, catalogue operations and partner support