Senior Backend Software Engineer, Twelve Labs

• Experience: 5+ years of backend engineering experience, with a proven track record of designing and delivering scalable web services and APIs
• API Expertise: Advanced proficiency in designing and implementing RESTful APIs, adhering to OpenAPI/Swagger specifications, with experience in modern frameworks (e.g., Go’s Gin or Echo, Spring Boot, or similar)
• Technical Expertise: Deep expertise in service-oriented architecture (SOA), microservices, and distributed systems, with strong knowledge of scalable database design (e.g., relational, NoSQL) and effective use of event-driven architecture
• Cloud Proficiency: Extensive experience with cloud-native development and deployment on platforms like AWS, GCP, or Azure, leveraging tools such as Docker, Kubernetes, or serverless frameworks to ensure scalability and resilience
• Analytical & Collaborative Skills: Strong first-principles thinking to address complex technical challenges, combined with effective communication skills and a collaborative approach to working with cross-functional teams
• Even if there are a few checkboxes that aren’t ticked through your prior experience, we still encourage you to apply! If you are a 0-1 achiever, a ferocious learner, and a kind and fun team player who motivates others, you will find a home at TwelveLabs

Desirable

• As a Senior Product Backend Engineer at Twelve Labs, you’ll architect scalable APIs and systems to power our AI video platform
• You’ll collaborate with cross-functional teams to integrate video foundation models, optimizing for performance and adaptability in a dynamic startup environment
• Design and implement scalable RESTful APIs adhering to OpenAPI specifications, powering features like video search, generation, and embedding, integrated with model inference pipelines
• Architect high-throughput, service-oriented backend systems to support enterprise-grade SaaS solutions for diverse customers, leveraging cloud-native tools (e.g., AWS, GCP, Azure)
• Optimize performance and reliability of distributed systems, processing large-scale video data with low latency and high availability
• Collaborate with cross-functional teams (product managers, frontend engineers, AI/ML teams) to deliver end-to-end video solutions
• Apply video-specific technologies (e.g., encoding, transcoding, streaming, metadata extraction) to enhance product capabilities and meet strategic goals