We are looking for a Backend / Post-Processing Engineer to join our engineering team.

You will work on the core processing pipeline that transforms raw test results, audio streams, signaling logs, and real-time metrics into meaningful reports, analytics, and alerts delivered to our customers.

Your work will directly impact the intelligence layer of our platform: reporting, analytics, monitoring, and audio-quality evaluation.

Tasks

• Design and implement backend logic for post-processing of test results and communication data
• Build & extend pipelines for advanced test analytics (voice quality metrics, audio analysis, MOS models, timing & signaling evaluation)
• Implement and optimize audio-engineering-related processing (signal analysis, codecs, waveform transforms, etc.)
• Work with infrastructure and deployment tools using Terraform and Docker

Requirements

• Python – primary language for data processing and analytics
• Go – high-performance backend services
• Perl – some legacy & core components (Mojolicious) you may interact with
• Terraform – infrastructure-as-code for our cloud environment
• Docker – containerized development and production deployment
• Experience with audio processing, telecom protocols (SIP, RTP), or test automation frameworks is a strong plus.
• Good communication skills in English; German is a plus.
• Ability to work in agile startup environments.
• AWS / Cloud-based environment experience

Benefits

• Work on cutting-edge automated testing and monitoring for real-time communication systems
• Shape the analytics and intelligence layer of a unique deep-tech product
• A modern tech stack with a fast-moving, engineering-focused
• Hybrid work model with flexibility. (Vienna/Graz/Home Office)
• Collaborative, friendly international team.
• Opportunities for deep learning in telecom, audio, and large-scale monitoring pipelines

Send us a message including

• a link to your LinkedIn profile or a CV, and…
• a summary of your accomplishments and/or a link to your Github

About the interview:

• Non-technical part (30min, video call)
• Technical part (1-2h, video call or on-site)