Senior AI Engineer (Voice & Conversational Systems)

We are looking for a Senior AI Engineer with hands-on experience in building production-grade conversational AI systems, with a strong focus on voice bots and contact center solutions. This is a voice-first role focused on real-time conversational systems — not a general backend or “LLM-only” development position. The successful candidate will help design and build advanced AI-driven voice systems that support live call environments and enhance real-time decision-making processes Key Responsibilities: • Lead technical design sessions and define architecture for voice and AI-based systems • Drive architectural decisions for scalable, low-latency conversational platforms • Mentor and support mid/junior engineers, enforcing best practices and coding standards • Collaborate with product and business stakeholders to shape delivery roadmaps • Own complex problem-solving in areas such as call flow optimization, latency reduction, and voice agent accuracy • Ensure security, compliance, and reliability in customer-facing systems • Build and maintain AI agents operating in event-driven and real-time environments • Participate in coding, testing, debugging, and production support. Required Skills & Experience: • 6+ years of commercial experience with Python, building scalable production systems • Strong expertise with backend frameworks such as Django, FastAPI, or Flask • Proven experience integrating LLM APIs into live applications • Hands-on experience with Amazon Connect and Amazon Lex (or comparable enterprise conversational platforms) • Experience building enterprise-grade voice bots and contact center integrations • Strong understanding of real-time system constraints and telephony integrations • Expertise in SQL/NoSQL data modeling, query optimization, and scaling systems for conversational workloads • Experience with CI/CD pipelines, Infrastructure as Code (Terraform or CloudFormation), Docker, Kubernetes, and monitoring tools. Nice to Have: • Recent hands-on experience with generative AI systems in production • Practical knowledge of testing and evaluating AI agents • Experience with model fine-tuning • Strong understanding of scalable system architecture (microservices, API orchestration, event-driven design) • Experience integrating STT (Speech-to-Text), TTS (Text-to-Speech), and NLP services into user-facing platforms • Flexibility working with different LLM models and frameworks