• Support and empower your team by contributing to a collaborative, inclusive, and respectful work environment • Partner with engineers and stakeholders to design and deliver scalable search and data solutions • Help bridge traditional lexical search and modern semantic search approaches • Design and implement hybrid search strategies combining keyword-based and vector-based retrieval • Work with vector databases to manage and query high-dimensional embeddings • Design and optimize retrieval-augmented generation (RAG) pipelines, including handling long documents and retrieval quality • Contribute to knowledge graph–driven approaches to enhance search relevance and data relationships • Build and maintain high-throughput streaming data pipelines (e.g., Kafka) for real-time ingestion and indexing • Contribute to architectural decisions that improve system scalability, reliability, and observability • Participate in a shared on-call rotation to support service reliability and incident response with a focus on learning and prevention • Collaborate with Product and Engineering to define technical requirements, timelines, and deliverables • Apply modern engineering practices, including Agile methodologies, CI/CD pipelines, and DevOps principles • Review code, identify areas for improvement, and help reduce technical debt • Troubleshoot and resolve production issues to maintain high availability and performance • Stay current with emerging technologies in search, AI, and data systems, and evaluate their impact • Deploy and manage applications in Kubernetes environments • Monitor application health and performance using tools such as Splunk, Datadog, and Grafana

• work on the core systems powering Synthesia’s script preview and voice generation experience • build and operate backend services that orchestrate multiple text-to-speech (TTS) providers • ensure provider reliability, request routing, and output consistency • contribute to user-facing product problems from a backend perspective • own projects that span multiple systems and domains • evaluate work through system performance and user experience metrics • collaborate closely with product, frontend, and R&D teams

• Work on end-to-end product features across the Avatars and Generative Media domain. • Design and deliver features that combine frontend, backend, and AI model capabilities. • Take ownership of features from idea through to production. • Work directly with AI models, understanding reliability constraints and shaping product decisions. • Build backend systems, frontend experiences, and end-to-end workflows. • Collaborate closely with product and design to translate user problems into experiments and features. • Ship features behind feature flags, measure outcomes, and refine based on feedback.

• Own the architecture and roadmap of the technical system. • Quickly become the go-to expert in new codebases. • Navigate ambiguity and turn complex problems into executable plans. • Jump in to lead frontend or infrastructure issues as needed. • Drive organizational progress through leadership roles such as ADRs and mentorship. • Prioritize end-user journey and business metrics.