Voice AI Engineer (Real-Time Speech)

• Azerbaijan, Europe, Georgia, Turkey, Ukraine
• Office/Remote
• Software Development
• Leading regional mobile network operator
• We are looking for a Voice AI Engineer (Real-time speech) to join our team!
• Cloud Foundation & Landing Zone: Deploy target hybrid network architectures, establishing a secure AWS Landing Zone Accelerator (LZA) and hybrid Data/AI platforms on AWS.
• AI Chatbot & Real-Time Voicebot Implementation: Develop and operationalize a flagship Customer Care Voicebot (STT → LLM → TTS pipeline) and Agentic Chatbot targeting
• Deploy and maintain production customer-trained Whisper (Azerbaijani ASR) and Azerbaijani TTS models as low-latency real-time endpoints on Amazon SageMaker and specialized GPU node pools (NVIDIA A100/L40S).
• 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 without API throttling.
• Establish LLMOps & MLOps pipelines using Amazon SageMaker Pipelines and MLflow for experiment tracking, model versioning, prompt/agent registries, automated evaluation harnesses, and RAG knowledge base retrieval.
• Build call and chat transcription pipelines to ingest, transcribe, and extract real-time insights (churn risk, dissatisfaction, intent, lead signals) into downstream decision layers.
• Enforce data sovereignty and privacy controls by integrating on-premises Format Preserving Encryption (FPE) and tokenization wrappers into ML pipelines so zero raw PII enters AWS cloud environments.
• 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 .
• Hands-on experience with EMR-on-EKS, Apache Iceberg, or MSK (Kafka) streaming pipelines.
• 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).

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