Roles and Responsibilities:
- AI Architecture Design: Define and design enterprise-level Generative AI architectures, integrating large language models (LLMs), multimodal systems, and AI-driven automation into business applications.
- Solution Development: Lead the development and deployment of GenAI solutions using state-of-the-art models (e.g., GPT, LLaMA, Claude, Gemini) for tasks such as content generation, summarization, code assistance, chatbots, and knowledge retrieval.
- Model Integration & Customization: Architect and implement fine-tuning, prompt engineering, and model orchestration strategies tailored to enterprise needs while ensuring scalability, performance, and security.
- MLOps & Deployment: Oversee MLOps pipelines for Generative AI workloads using tools like MLflow, Kubernetes, Docker, and cloud platforms such as AWS, Azure, or GCP.
- Data Governance & Compliance: Ensure responsible AI usage by implementing governance frameworks, ethical AI practices, and data security policies aligned with organizational and regulatory standards.
- Cross-Functional Collaboration: Work closely with data engineering, application development, and business teams to align AI capabilities with strategic goals.
- Innovation & Research: Stay ahead of industry trends in GenAI, LLMs, and multimodal models; evaluate emerging frameworks and technologies to drive continuous innovation.
- Mentorship & Leadership: Mentor AI engineers and data scientists, provide architectural guidance, and establish best practices for AI solution design and deployment.
