Cresta

Infrastructure Engineer/SRE role focused on building and advancing core infrastructure for an AI company. Responsibilities include developer toolchain, ensuring reliability of Kubernetes clusters, metrics/logging/alerting, infrastructure-as-code, automation, and building ML infrastructure for AI teams.

Junior Software Engineer Intern role focused on building and improving backend services for real-time AI features and search, designing APIs, and contributing across the full stack. Requires a CS degree, backend language proficiency, and API experience. Internship is 3 months with potential for full-time conversion.

The Infrastructure Engineer/SRE role at Cresta focuses on designing, building, and advancing core infrastructure to support engineering teams. Responsibilities include developing dev tools, ensuring reliability of Kubernetes clusters, implementing metrics and logging, managing infrastructure-as-code deployments, automating operations, and building machine learning infrastructure for AI teams.

Infrastructure Engineer/SRE role focused on building and advancing core infrastructure for an AI company, including developer toolchains, Kubernetes clusters, logging, and infrastructure-as-code. The role specifically involves building machine learning infrastructure to support AI teams in training, testing, and deploying models on large-scale datasets.

Senior Backend Engineer for Cresta's Voice Platform team, focusing on designing, scaling, and operating distributed services for real-time voice infrastructure and contact center automation. Responsibilities include leading development of microservices in Golang, owning voice platform integrations, expanding capabilities like SIP/WebRTC/multilingual support/transcription/translation, building conversation intelligence systems, and improving observability and reliability of real-time voice pipelines. Requires strong backend and distributed systems experience, Go expertise, and cloud infrastructure knowledge.

Staff Infrastructure Software Engineer responsible for designing, building, and advancing core infrastructure, including multi-cloud Kubernetes clusters, developer toolchains, and automation. The role specifically involves building machine learning infrastructure to support AI teams in training, testing, and deploying models on large-scale datasets, with a bonus for GPU-enabled cluster experience.