Solution Architect – AI Infrastructure & Private Cloud

Job Description

Key Responsibilities :

– Design and implement end-to-end AI infrastructure solutions, encompassing compute, storage, networking, and security, tailored to specific client needs and workloads.

– Develop and maintain comprehensive architectural blueprints, standards, and best practices for AI/ML infrastructure deployments across various cloud platforms (AWS, Azure, GCP) and private cloud environments.

– Collaborate with data scientists and machine learning engineers to optimize infrastructure for model training, inference, and deployment, ensuring optimal performance and resource utilization.

– Lead the evaluation and selection of appropriate hardware and software technologies, including GPUs, specialized processors, and AI/ML platforms, based on performance, cost, and scalability considerations.

– Drive the adoption of MLOps and DevOps principles to automate the deployment, monitoring, and management of AI/ML models in production, ensuring reliability and efficiency.

– Provide technical leadership and mentorship to junior architects and engineers, fostering a culture of innovation and continuous learning within the team.

– Engage with clients to understand their business challenges and translate them into technical requirements, presenting architectural solutions and recommendations in a clear and concise manner.

– Stay abreast of the latest advancements in AI/ML infrastructure, cloud technologies, and industry best practices, proactively identifying opportunities to improve our solutions and services.

Required Skillset :

– Demonstrated ability to design and implement scalable, secure, and high-performance AI infrastructure solutions on AWS, Azure, GCP, or private cloud environments.

– Proven expertise in architecting and deploying AI/ML workloads, including model training, inference, and deployment, using technologies such as Kubernetes, Docker, and serverless computing.

– Deep understanding of MLOps and DevOps principles, with experience in automating the deployment, monitoring, and management of AI/ML models in production.

– Strong knowledge of hardware and software technologies relevant to AI/ML, including GPUs, specialized processors, AI/ML platforms, and data storage solutions.

– Excellent communication, presentation, and interpersonal skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.

– Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

– 10-20 years of experience in Solution Architecture, Cloud Architecture, or a related role, with a focus on AI/ML infrastructure.

Are you interested in this position?

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