About the Role :
We are seeking an innovative and strategic Generative AI Architect to lead the design and implementation of cutting-edge generative AI solutions across our enterprise.
The ideal candidate will have deep expertise in artificial intelligence, natural language processing, and generative models (such as GPT, DALLE, or other transformer architectures), with a proven ability to architect scalable AI systems that drive business value.
Key Responsibilities :
- Architect end-to-end generative AI solutions that integrate with existing enterprise systems and workflows.
- Lead the design, development, and deployment of generative models including language models, image synthesis, code generation, and other AI-driven creative applications.
- Collaborate with data scientists, ML engineers, software developers, and business stakeholders to translate business needs into scalable AI architectures.
- Develop AI model training pipelines, fine-tuning workflows, and performance optimization strategies.
- Ensure robust data governance, security, and compliance in AI model development and deployment.
- Evaluate and select appropriate AI frameworks, cloud services, and hardware infrastructure to support generative AI workloads.
- Provide technical leadership and mentorship to AI teams and stakeholders.
- Stay updated with the latest advances in generative AI research and industry trends to drive innovation.
- Define best practices and standards for generative AI architecture and integration.
Required Skills and Qualifications :
Bachelors or Masters degree in Computer Science, AI, Machine Learning, Data Science, or related field.4+ years of experience in AI / ML architecture, software engineering, or related roles.Strong expertise in generative AI models such as GPT, BERT, Transformer architectures, GANs, VAEs.Proficiency in Python and AI / ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers.Experience designing scalable AI infrastructure using cloud platforms (AWS, Azure, GCP) and MLOps tools.Deep understanding of NLP, computer vision, and deep learning techniques.Familiarity with distributed training, model optimization, and deployment best practices.Strong knowledge of API design and microservices architecture for AI systems.Experience with data engineering, model versioning, and experiment tracking.Excellent problem-solving, communication, and leadership skills(ref : hirist.tech)