Generative AI-Director - Operations

Experience: 14 plus Years

Location: Offshore

Job Type: Full-time

Department: Artificial Intelligence / Data Science / R&D

Reports To: Head of AI / CTO / Chief Data Officer

Role Overview

We are seeking an experienced and visionary Generative AI Lead to spearhead our advanced AI initiatives, specializing in generative models such as GPT, DALLE, and other cutting-edge architectures. With over 14 years of experience, you will guide AI strategy, lead the design and deployment of generative AI solutions, and drive innovation to deliver transformative business value.

This role demands deep expertise in machine learning, natural language processing, and computer vision, combined with strong leadership to manage cross-functional teams and influence stakeholders. Lead the strategy, architecture, and execution of generative AI initiatives aligned with business goals.

Design, develop, and optimize generative AI models (NLP, vision, multimodal) using frameworks like TensorFlow, PyTorch, or others.

Collaborate with data engineering, product, and research teams to integrate generative AI capabilities into scalable solutions.

Drive innovation by exploring new generative AI technologies and methodologies, including prompt engineering, fine-tuning, and transfer learning.

Oversee data preparation, model training, evaluation, and deployment processes ensuring quality and performance.

Define best practices for AI governance, ethical AI use, and compliance with data privacy regulations.

Mentor AI/ML engineers and data scientists, fostering a culture of continuous learning and experimentation.

Present AI strategies, technical approaches, and project updates to senior leadership and stakeholders. Masters or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

14+ years of experience in AI/ML with a focus on generative AI models and applications.

Proven track record leading AI teams and delivering enterprise-grade AI solutions.

Expertise in transformer-based models (GPT, BERT, etc.), GANs, VAEs, diffusion models, or similar architectures.

Proficiency with ML frameworks such as TensorFlow, PyTorch, Hugging Face Transformers.

Strong programming skills in Python, and familiarity with CUDA, distributed training, and cloud ML platforms (AWS SageMaker, GCP AI Platform, Azure ML).

Deep understanding of NLP, computer vision, multimodal learning, and data pipelines.

Experience with MLOps, model versioning, monitoring, and lifecycle management.

Strong communication and stakeholder management skills.

Experience in ethical AI frameworks, bias mitigation, and regulatory compliance.