GenAI Dev Lead

Job Summary

We are currently seeking a GenAI Dev Lead to join our team in Bangalore, Karntaka (IN-KA), India (IN).

Key Responsibilities

• Develop, and implement AI/ML and Generative AI solutions across various domains, including prediction systems, recommendation engines, text analytics, computer vision, chatbots, and content intelligence platforms.
• Build and deploy advanced ML models using frameworks such as TensorFlow, PyTorch, Keras, SpaCy, and scikit-learn.
• Apply deep knowledge of statistics, machine learning, NLP, and generative models including GANs and transformers.
• Work with RAG (Retrieval-Augmented Generation) techniques.
• Collaborate with cross-functional teams to design and implement end-to-end AI pipelines, from data ingestion to model deployment and monitoring.
• Support the development of GenAI use cases, prototypes, and POCs tailored to specific industry requirements.
• Communicate technical concepts clearly and effectively with both technical and non-technical stakeholders.
• Engage with clients to understand business needs and deliver customized AI/ML solutions that drive value.
• Stay current with trends and advancements in AI, GenAI, LLMs, and related fields.
• Contribute to the development of frameworks, capabilities, and features for NTT DATA's global GenAI platform and TechHub.

Minimum Qualifications

• Masters in AI from a reputed College / University
• Demonstrated using Python and relevant packages for ML and data science in multiple real projects that is not limited to their own personal development environment.
• Strong fundamentals in building GenAI solutions, preferably using Agentic frameworks.
• Deep knowledge in Predictive Analytics
• Machine Learning and Deep Learning
• Generative AI
• Agentic systems
• ML Ops / AI Infrastructure
• Strong understanding of LLM technologies, embedding models, cloud-based AI services, and AI/ML operations.
• Hands-on experience with cloud-based AI platforms, including Azure OpenAI, Google Vertex Gen AI, and AWS AI services.

Soft Skills

• Strong problem-solving skills and critical thinking.
• Effective communicator capable of translating complex AI topics to stakeholders.
• Self-driven, collaborative, and adaptable to fast-paced environments.