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N-iX
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Voice AI Engineer (Real-Time Speech)

SageMakerNVIDIA A100L40SWhisperAWS BedrockAvayaGenesysPelatroPythonRedisTerraformCDKGitLab CIDockerKubernetesAWS EKSMLflowAmazon CloudWatchSplunkSageMaker PipelinesSageMaker Feature StoreSageMaker Model RegistryBedrock AgentCoreBedrock GuardrailsBedrock Knowledge BasesEMR-on-EKSApache IcebergMSKKafka
Формат
Remote
Зайнятість
-
Локація
Kyiv
Оплата
Не вказана

Про позицію

N-iX is seeking a Voice AI Engineer for a project with a major Azerbaijani telecommunications company. The role involves building a real-time voicebot pipeline (STT → LLM → TTS) on AWS, integrating with enterprise telephony platforms, and ensuring data privacy compliance.

Обовʼязки

  • Design, build, and operationalize end-to-end real-time STT → LLM → TTS voicebot pipelines on AWS.
  • Deploy and maintain production customer-trained Whisper (Azerbaijani ASR) and Azerbaijani TTS models as low-latency endpoints on Amazon SageMaker and GPU node pools.
  • Implement and manage the Bedrock Proxy Gateway on EKS for multi-model routing, priority queuing via Redis Sorted Sets, cost caps, and high-availability serving targeting ~200 rps.
  • Integrate voicebot and chatbot decision engines with Avaya, Genesys, and Pelatro.
  • Establish LLMOps & MLOps pipelines using Amazon SageMaker Pipelines and MLflow.
  • Build call and chat transcription pipelines to ingest, transcribe, and extract real-time insights.
  • Enforce data sovereignty and privacy controls by integrating on-premises FPE and tokenization wrappers.
  • Define NFR baselines, dialogue flows, voicebot persona, turn-taking, and fallback/escalation logic.
  • Automate ML deployment workflows using GitLab CI/CD and Infrastructure-as-Code (Terraform or AWS CDK), establishing observability and FinOps spend/anomaly monitoring via Amazon CloudWatch and Splunk.

Вимоги

  • 4+ years of hands-on experience with machine learning and Speech Processing with a primary focus on real-time conversational AI, ASR (STT), and TTS voice pipelines.
  • Deep expertise with Amazon SageMaker (real-time GPU inference endpoints, Pipelines, Feature Store, Model Registry) and Amazon Bedrock (AgentCore, Bedrock Guardrails, Knowledge Bases).
  • Proven track record in streaming speech inference, speech synthesis, and low-latency audio processing.
  • Strong experience in GPU optimization and containerized orchestration (NVIDIA A100/L40S, AWS EC2 GPU instances, Docker, Kubernetes/EKS).
  • Solid understanding of contact center and telephony platform integrations (Avaya, Genesys) and real-time decisioning interfaces.
  • Proficient in Python, Redis (priority queuing & caching), and data security/privacy (FPE tokenization, handling sensitive/PII data).
  • AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect. (nice-to-have)
  • Hands-on experience with EMR-on-EKS, Apache Iceberg, or MSK (Kafka) streaming pipelines. (nice-to-have)
  • Strong critical thinking, problem-solving, and analytical skills with ownership of mission-critical, low-latency deliverables.
  • Excellent communication and collaboration skills to work closely with cross-functional teams (AI Architects, Data Engineers, CC SMEs, and Security/Compliance).
  • Results-oriented, proactive mindset with strong ownership within an Agile / Scrum framework.
  • Upper-Intermediate+ English level (written and spoken).

Переваги

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

До кого писати

Voice AI Engineer (Real-Time Speech)
Оригінал