Voice AI Engineer

Company Description Shuru is a Product, AI, and Technology Consulting company that helps startups and enterprises build, scale, and modernize their digital products with high-performance engineering teams. The company delivers AI-native solutions across AI and automation, API development, cloud and DevOps, custom software, data engineering, and product engineering services. Founded by former leaders from Gojek, Flipkart, and Argor VC, Shuru is focused on making world-class, outcome-driven, AI-powered engineering accessible to businesses of all sizes. Its teams have built technology for leading brands such as Gojek, Halodoc, Flipkart, and Mosaic, driving measurable business impact through modern engineering. With offices in India, UAE, Singapore, and Canada, Shuru combines global expertise with local insight to move clients from idea to impact.

Role Description The Voice AI Engineer is a full-time, on-site role based in Bengaluru, focused on designing, building, and optimizing voice-driven AI solutions for Shuru’s clients. Day-to-day responsibilities include developing and integrating speech and language models, implementing voice assistants and conversational interfaces, and collaborating with product and engineering teams to translate business requirements into robust voice AI features. The role involves researching and experimenting with state-of-the-art NLP and speech technologies, improving model performance through pattern recognition and data-driven evaluation, and ensuring scalability, reliability, and security of deployed systems. The Voice AI Engineer will also participate in code reviews, maintain clean and well-documented codebases, and contribute to technical discussions and architectural decisions across projects.

Qualifications

• Strong foundation in

Computer Science principles and

Software Development , including data structures, algorithms, and production-grade coding.

• Experience with

Neural Networks and modern machine learning frameworks for building and deploying voice or conversational AI models.

• Applied expertise in

Natural Language Processing (NLP) , including intent detection, entity recognition, and dialogue systems.

• Proficiency in

Pattern Recognition techniques for analyzing audio and language data, improving model accuracy, and handling noisy inputs.

• Hands-on experience with Python or similar languages, and familiarity with ML/AI libraries (e.g., TensorFlow, PyTorch, Hugging Face, spaCy).
• Knowledge of speech processing tools and services (e.g., ASR, TTS engines, cloud-based voice APIs) and integrating them into applications.
• Experience building scalable microservices or APIs, and working with cloud platforms (AWS, GCP, or Azure) and CI/CD workflows.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data