Backend Engineer - Embedded and Audio Ai

Backend Engineer – Embedded and Audio Ai Location: Jordan   The Opportunity Reporting to the Lead Backend Engineer, you will design business specific software components and modules using appropriate modelling techniques in line with agreed software design standards, patterns, and methodology.
As Backend Engineer specializing in Embedded and Audio AI, you will build scalable services for audio data ingestion, processing, and model integration to power our AI-enabled platforms.
  Key Responsibilities ·        Design and implement backend services tailored to embedded audio ingestion , real-time signal processing , and AI inference workflows ·        Develop solutions that support audio optimization —minimizing latency, maximizing clarity, and reducing unnecessary transmission or computation overhead ·        Build and manage automated audio workflows , including scheduled recordings, voice activity detection (VAD), event-based triggering, and batch inference ·        Integrate with DSP or edge firmware layers to support preprocessing, filtering, and format conversion (e.
g., PCM ↔ Opus/WAV) ·        Model and simulate system behaviour under constrained environments (low power, intermittent connectivity, real-time requirements) ·        Design, code, verify, test, document, amend and refactor backend modules handling audio metadata , telemetry , and stream segmentation ·        Support device registration, identity mapping, OTA updates, and telemetry reporting through secure and scalable APIs ·        Ensure integration with message brokers (e.
g., MQTT, AMQP) and low-power IoT protocols for audio event reporting ·        Participate in discussions with hardware, ML, and product teams to align system-level architecture with feature-level goals ·        Maintain deep knowledge of audio data flow, real-time backend infrastructure, inference runtimes (e.
g., ONNX Runtime, TensorFlow Lite), and signal quality metrics ·        Build reusable audio-centric libraries and tools for logging, normalization, feature extraction, and timestamp alignment Comply with QHSE (Quality Health Safety and Environment), Business Continuity, Information Security, Privacy, Risk, Compliance Management and Governance of Organizations policies, procedures, plans, and related risk assessments.
Class A medical Insurance Requirements: -        Bachelor’s Degree in Computer Engineering, Electrical Engineering, Embedded Systems, or related fields -        5-8 years of experience in backend or embedded systems development with strong computer science fundamentals -        At least 3 years working in Agile teams , preferably in AI , edge computing , or audio processing domains -        Strong in at least one backend language: Python , Go , C++ , or Rust -        Experience integrating with audio AI libraries , inference runtimes (e.
g., ONNX Runtime, TensorRT), or DSP frameworks -        Understanding of audio data formats (PCM, WAV, Opus) and protocols for streaming (e.
g., RTP, WebRTC, HTTP2) -        Proficiency in containerization (Docker) and orchestration in embedded/kubernetes-like edge environments -        Experience working with time-series or binary-structured data in PostgreSQL , TimescaleDB , or flat file systems -        Experience with backend APIs that handle audio metadata, device telemetry, or embedded commands over REST or MQTT -        Fluent English and Arabic is required