Generative AI Engineer

Sonata Software Overview In today's market, there is a unique duality in technology adoption. On one side, extreme focus on cost containment by clients, and on the other, deep motivation to modernize their Digital storefronts to attract more consumers and B2B customers. As a leading Modernization Engineering company, we aim to deliver modernization-driven hypergrowth for our clients based on the deep differentiation we have created in Modernization Engineering, powered by our Lightening suite and 16-step Plat formation™ playbook. In addition, we bring agility and systems thinking to accelerate time to market for our clients. Headquartered in Bengaluru, India, Sonata has a strong global presence, including key regions in the US, UK, Europe, APAC, and ANZ. We are a trusted partner of world-leading companies in BFSI (Banking, Financial Services, and Insurance), HLS (Healthcare and Lifesciences), TMT (Telecom, Media, and Technology), Retail & CPG, and Manufacturing space. Our bouquet of Modernization Engineering Services cuts across Cloud, Data, Dynamics, Contact Centers, and around newer technologies like Generative AI, MS Fabric, and other modernization platforms. Job Summary We are seeking a highly skilled and motivated AI Solutions Engineer with a strong background in designing and developing AI-driven applications. The ideal candidate will have hands-on experience with modern AI frameworks, cloud platforms, and deployment pipelines, and will be passionate about building scalable and intelligent systems. Key Responsibilities Design and develop robust AI solutions using Python, TensorFlow, and PyTorch. Build and maintain AI pipelines for training, evaluation, and deployment. Implement Retrieval Augmented Generation (RAG) and prompt engineering techniques to enhance model performance. Work with AI Foundry, Fabric Data Agents, or Copilot Studio to integrate intelligent capabilities into enterprise systems. Deploy models and services using Azure ML Studio, Docker, and CI/CD pipelines. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Ensure scalability, reliability, and performance of AI systems in production environments. Required Qualifications 3+ years of professional experience in AI solution development. Proficiency in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience designing end-to-end AI pipelines including data ingestion, model training, evaluation, and deployment. Familiarity with RAG architecture and prompt engineering. Hands-on experience with at least one of the following: AI Foundry, Fabric Data Agents, or Copilot Studio. Strong understanding of cloud platforms and DevOps practices, especially Azure ML Studio, Docker, and CI/CD. Preferred Skills Experience working in agile development environments. Knowledge of MLOps practices and tools. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Regards Mizbha Firdose

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