Gen AI Solution Architect

Job Description

GenAI Architect - Fulltime Remote Shift:General Shift Job Summary: We are looking for a GenAI Architect with deep expertise in AI/Gen AI systems, specifically in designing and building large-scale AI solutions. As a GenAI Architect , you will be responsible for leading the design and architecture of cutting-edge Gen AI systems, with a focus on large language models (LLMs), AI frameworks, and advanced machine learning technologies. This is a senior role requiring strategic vision and hands-on expertise in AI solution architecture, software engineering, and MLOps practices. Responsibilities: Architecting AI Solutions : Design and architect scalable, efficient, and robust GenAI systems leveraging advanced machine learning frameworks, particularly in large language models (LLMs). Leading AI Framework Implementation : Lead the design and implementation of complex GenAI models and frameworks using Python and other relevant technologies. Provide strategic oversight of AI/GenAI architecture to align with business needs and tech stack. Model Optimization and Performance : Oversee the optimization of large-scale AI models for both training and inference, ensuring high performance and scalability across platforms. API Architecture & Development : Guide the development of high-performance APIs for AI services using FastAPI or other relevant frameworks, ensuring ease of integration with internal and external systems. MLOps Integration : Drive the integration of MLOps pipelines for seamless deployment, monitoring, and scaling of machine learning models, ensuring automation, efficiency, and high availability. Leadership and Mentorship : Provide technical leadership and mentorship to teams of engineers, guiding them in best practices for AI system architecture, software engineering, and AI model lifecycle management. Collaboration with Cross-Functional Teams : Work closely with Data Science, Data Engineering, DevOps, and Product teams to ensure AI/Gen AI solutions are architected in a way that meets both technical and business requirements. CI/CD & Automation : Design and implement automated pipelines for continuous integration and continuous deployment (CI/CD) of AI models, ensuring smooth and rapid updates to production environments. DevOps Practices : Ensure the robust deployment and management of AI models in production environments using DevOps tools like Docker, Kubernetes, Jenkins, and Terraform. Security and Compliance : Ensure AI systems adhere to best practices in security, privacy, and compliance, especially in handling sensitive data and large-scale model training. Key Requirements: Experience : Hands-on experience in AI/Gen AI system design, implementation, and scaling, with expertise in large language models (LLMs) and AI frameworks. Programming Skills : Expertise in Python and a strong understanding of data manipulation libraries like Pandas and NumPy. AI Frameworks : Experience in designing and managing large-scale AI models using cutting-edge frameworks such as TensorFlow, PyTorch, and similar. API Development : Strong experience in FastAPI or other modern frameworks for building high-performance APIs. Software Engineering : Proficient in software engineering principles, version control (Git), and maintaining code quality through automated testing and CI/CD pipelines. MLOps & ML Engineering : Deep understanding of MLOps practices for model deployment, monitoring, and optimization. Hands-on experience with ML engineering workflows. DevOps Expertise : Strong experience with DevOps tools like Docker, Kubernetes, Jenkins, and Terraform, with an emphasis on automating deployment and managing infrastructure at scale. Leadership & Mentorship : Proven experience in leading technical teams, making architectural decisions, and mentoring junior engineers.