Senior Generative AI Engineer

Role Description The Senior Generative AI Engineer will design, develop, and deploy generative AI models and systems that support key product and platform initiatives. In this full-time hybrid role based in the Greater Bengaluru Area, the engineer will spend part of the time working on-site with cross-functional teams and part of the time working from home. Day-to-day responsibilities include researching and prototyping generative model architectures, fine-tuning large language and multimodal models, and building scalable APIs and services to integrate these models into production applications. The role involves collaborating with product managers, designers, and other engineers to translate business requirements into robust technical solutions, as well as monitoring model performance, optimizing inference pipelines, and addressing reliability, safety, and bias concerns. The engineer will also contribute to code reviews, technical documentation, and mentorship of junior team members, helping establish best practices for generative AI within the organization.
Qualifications
Strong background in machine learning and deep learning, including experience with large language models, generative architectures (e.g., transformers, diffusion models), and modern training techniques.
Proficiency in programming languages commonly used in AI development (such as Python) and frameworks like PyTorch, TensorFlow, or JAX, with experience building production-grade ML systems.
Solid understanding of data engineering and MLOps practices, including dataset preparation, feature engineering, model deployment, monitoring, and continuous integration/continuous delivery for ML pipelines.
Experience designing and consuming RESTful or GraphQL APIs, integrating AI services into cloud-native applications, and working with cloud platforms (e.g., AWS, GCP, Azure) for scalable model serving.
Knowledge of responsible AI principles, including model evaluation, bias detection, safety guardrails, prompt engineering, and techniques to improve reliability and alignment of generative models.
Strong problem-solving and analytical skills, with the ability to translate product and business needs into clear technical requirements and experiment designs.
Effective communication and collaboration skills, with experience working in cross-functional teams and mentoring other engineers or data scientists.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial

Work arrangement
Yes