Teams at Lutra

Design and lead end-to-end architectures for production machine-learning systems at extraordinary scale. Responsibilities span data preparation, feature generation, model delivery, deployment, hosting, inference, monitoring, performance optimization, and technical design. The role establishes engineering standards, influences ML architecture, and collaborates across data science and software engineering to build reliable, maintainable systems for high-volume, low-latency workloads.

Design and operate globally distributed database systems across bare-metal and cloud environments. Lead reliability, performance, automation, observability, incident response, capacity planning, security, and database change management. Establish technical direction, simplify the infrastructure footprint, develop data-platform roadmaps, troubleshoot complex distributed-system failures, and mentor engineers across teams.

Design and build real-time, highly concurrent software and cloud-native systems for an AI-powered emergency communications platform. Integrate and deploy LLMs, optimize voice and audio-processing pipelines, and support speech recognition, synthesis, detection, and filtering. Contribute to infrastructure, observability, security, scalability, and fault tolerance. Provide technical leadership through architecture decisions, code reviews, mentoring, and engineering best practices.