AI Architect

As an AI Architect at the company, you will play a pivotal role in defining and implementing the end-to-end architecture for deploying machine learning models. This includes advanced Generative AI and LLM solutions. Your leadership will be key in guiding a talented cross-functional team of Data Scientists, Backend Developers, and DevOps Engineers towards innovation, technical excellence, and operational efficiency. - **Architectural Leadership:** - Design, develop, and own the scalable, secure, and reliable end-to-end architecture for deploying and serving ML models, with a focus on real-time inference and high availability. - Lead the strategy and implementation of the in-house API wrapper infrastructure for exposing ML models to internal and external customers. - Define architectural patterns, best practices, and governance for MLOps, ensuring robust CI/CD pipelines, model versioning, monitoring, and automated retraining. - Evaluate and select the optimal technology stack for our ML serving infrastructure, balancing performance, cost, and maintainability. - **Team Leadership & Mentorship:** - Lead, mentor, and inspire a diverse team through complex architectural decisions and technical challenges. - Foster a collaborative environment that encourages knowledge sharing, continuous learning, and innovation. - Drive technical excellence, code quality, and adherence to engineering best practices. - **Generative AI & LLM Expertise:** - Architect and implement solutions for deploying Large Language Models (LLMs) efficiently. - Drive the adoption of techniques like Retrieval Augmented Generation (RAG) to enhance LLM capabilities. - Develop strategies for fine-tuning LLMs for specific tasks and domain adaptation. - Stay updated on the latest advancements in Generative AI and evaluate their applicability to our business needs. - **Collaboration & Cross-Functional Impact:** - Collaborate closely with Data Scientists to optimize models for production. - Partner with Backend Developers to build robust APIs for ML predictions. - Work with DevOps Engineers to automate deployment and scaling of the AI infrastructure. **Requirements:** - **Education:** Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field. - **Experience:** - 10+ years in software engineering, with at least 5+ years in an Architect or Lead role. - Proven experience leading cross-functional engineering teams. - Experience in designing and deploying scalable ML model serving infrastructure. In summary, your role as an AI Architect will involve leading the architectural design and implementation of cutting-edge AI solutions, mentoring a talented team, and ensuring successful deployment of ML models in a production environment. Your expertise in Generative AI, LLMs, MLOps, and technical leadership will be crucial in driving innovation and excellence within the organization.,