Staff Software Engineer, Twelve Labs

• 10+ years of professional software engineering experience building applications and tools for government customers, with features such as auditable workflows, secure authentication, and role-based access controls
• Backend: Deep knowledge of service-oriented architecture (SOA), RESTful APIs, microservices, and distributed systems. Strong understanding of scalable database design (relational and NoSQL). Familiarity with industry standard authentication and authorization techniques
• AI Inference: Deep knowledge and experience building and integrating with custom model inference engines using the Torch framework in Python, Rust, or Go
• Polyglot: Familiar with developing polyglot microservices in a monorepo using GitFlow best practices
• Infra: Familiar with Docker, Kubernetes, and infrastructure scaling for containerized applications using GPUs. Exposure to IaC tools (ex. Helm, Docker Compose, Terraform), and observability tools (ex. Prometheus, OpenTelemetry, Grafana)
• Strong analytical, problem-solving, and first-principles thinking for tackling complex technical challenges
• Exceptional communication skills, able to clearly articulate technical concepts to technical and non-technical stakeholders
• Thrives in agile, fast-paced environments, demonstrating adaptability, resilience, and a strong ownership mindset
• 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

• We're looking for a Software Engineer with strong backend expertise to join our Government pod, helping deliver state-of-the-art TwelveLabs' models and products for U.S. public-sector customers
• You'll play a key role in designing, building, and scaling systems that power our platform end-to-end — from robust APIs and data pipelines to custom model inference engines
• You will ensure that our platform can deploy in both secure cloud and on-premise environments as a self-managed containerized solution
• The work blends deep engineering with security and compliance understanding designed to meet FedRAMP, CMMC, and DoD SRG Impact Levels
• You'll build for constrained networks and hardware, rigorous supply-chain practices, and high-reliability operations
• Backend Systems & APIs: Design and implement scalable RESTful APIs (OpenAPI-compliant) that power features such as embedding, indexing, search and video analysis, integrating with model inference pipelines
• System Architecture: Architect and optimize high-throughput, service-oriented backend systems for enterprise-grade Kubernetes deployments to ensure low latency, high availability, and scalability
• Cross-Functional Collaboration: Partner with Machine Learning engineers, Infrastructure Engineers and Forward Deployed Engineers to deliver end-to-end solutions, ensuring smooth integration between backend systems, AI pipelines, and user interfaces
• Quality & Standards: Drive adherence to coding standards, best practices, and optimization techniques across the stack, delivering high-quality, reliable, and maintainable systems

• Interviewing in person in San Francisco will be required