AI Architect

As an AI Architect at our organization, you will play a crucial role in defining and implementing the end-to-end architecture for deploying our machine learning models, including advanced Generative AI and LLM solutions, into production. Your responsibilities will include leading and mentoring a cross-functional team of Data Scientists, Backend Developers, and DevOps Engineers to foster a culture of innovation, technical excellence, and operational efficiency. In terms of Architectural Leadership, you will design, develop, and own the scalable, secure, and reliable architecture for deploying and serving ML models with a focus on real-time inference and high availability. You will also lead the strategy and implementation of the in-house API wrapper infrastructure and define architectural patterns, best practices, and governance for MLOps. Evaluating and selecting the optimal technology stack for our ML serving infrastructure will also be a key part of your role. Regarding Team Leadership & Mentorship, you will lead, mentor, and inspire the diverse team, guiding them through complex architectural decisions and technical challenges. Your goal will be to foster a collaborative environment that encourages knowledge sharing, continuous learning, and innovation across teams while driving technical excellence and adherence to engineering best practices. Your expertise in Generative AI & LLM will be essential as you architect and implement solutions for deploying Large Language Models, drive the adoption of techniques like Retrieval Augmented Generation, and stay updated on the latest advancements in AI to evaluate their applicability to our business needs. Collaborating closely with Data Scientists, Backend Developers, and DevOps Engineers will be crucial to integrate models seamlessly into the serving infrastructure, build robust APIs, and ensure operational excellence of the AI infrastructure. Effective communication of complex technical concepts to both technical and non-technical stakeholders will also be a part of your responsibilities. In terms of qualifications, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field, along with 10+ years of software engineering experience and proven experience in leading cross-functional engineering teams. Your technical skills should include expertise in MLOps principles, Python proficiency, containerization technologies, cloud platforms, Large Language Models, and monitoring tools. Leadership qualities such as exceptional mentorship and team-building abilities, strong analytical and problem-solving skills, excellent communication skills, and a strategic mindset will be highly valued in this role. Bonus points will be awarded for experience with specific ML serving frameworks, contributions to open-source projects, and familiarity with data governance and compliance in an AI context.,