IVR Systems Operations Engineer Sr

IVR Systems Operations Engineer Sr Required Qualifications Extensive Industry Experience: Proven experience (e.g. 5+ years) in software development and architecture, building large-scale AI or cloud-based solutions in production environments. AI & Voice Expertise: Hands-on expertise with AI/ML technologies, including natural language processing (NLP) or speech recognition. Familiarity with large language models (e.g., GPT, Claude or similar) and conversational AI/voice assistant development. Microsoft Azure and AWS Proficiency: Strong experience developing with Microsoft Azure and AWS cloud services. Knowledge of CI/CD, Azure and AWS container services for deploying AI workloads. Programming & DevOps Skills: Proficient in modern programming languages (such as Python, Java, C#, or similar) and building APIs or microservices. Solid understanding of DevOps and CI/CD practices (e.g., Azure DevOps pipelines) to ensure frequent, reliable delivery of AI software. System Design & Architecture: Deep knowledge of scalable, distributed systems design and cloud-native architecture. Experience implementing microservices, containerization, and API integration. Problem Solving & Innovation: Strong analytical and problem-solving skills with the ability to navigate complex technical challenges. Innovative mindset to drive continuous improvement and to evaluate emerging technologies for potential adoption. Communication: Excellent communication skills, with ability to explain complex AI solutions and technical strategies to diverse stakeholders. Preferred Qualifications Financial Services Familiarity: Experience working in banking, fintech, or other heavily regulated industries and understanding of compliance, security, and data privacy considerations for AI solutions in these environments. AI Research & Innovation: Demonstrated interest in emerging AI trends (such as agentic AI , multi-modal models , reinforcement learning , etc.) and experience bringing new AI concepts from prototype to production. Advanced Degree: Master’s or higher degree in Computer Science, Engineering, AI, or related field (or equivalent practical experience) is a plus. Preferred Qualifications Financial Services Familiarity: Experience working in banking, fintech, or other heavily regulated industries and understanding of compliance, security, and data privacy considerations for AI solutions in these environments. AI Research & Innovation: Demonstrated interest in emerging AI trends (such as agentic AI , multi-modal models , reinforcement learning , etc.) and experience bringing new AI concepts from prototype to production. Advanced Degree: Master’s or higher degree in Computer Science, Engineering, AI, or related field (or equivalent practical experience) is a plus.