Job
Description
As the Director of AI Platform & MLOps, you will play a crucial role in leading a team of engineers to architect, scale, and manage the infrastructure supporting AI Training Data Services. Your responsibilities will include translating the long-term vision into a technical roadmap, designing and implementing MLOps frameworks, managing multi-cloud infrastructure, and ensuring high availability and security of the platform. Key Responsibilities: - Translate the long-term vision into an executable technical roadmap, making key architectural decisions for the platform. - Lead the hands-on design and implementation of MLOps/LLMOPs framework, including CI/CD for models, data/model versioning, automated workflows, and monitoring. - Engineer and manage a scalable, multi-cloud infrastructure (AWS/GCP/Azure) using Infrastructure as Code (IaC) principles (Terraform, CloudFormation). - Oversee the technical integration, scaling, and reliability of data annotation platforms and the GIG worker technology layer. - Drive SRE best practices to ensure high availability, performance, and security of the entire platform. Team & Operational Leadership: - Recruit, lead, mentor, and directly manage a team of Cloud, DevOps, MLOps, and Site Reliability Engineers. - Foster a culture of technical excellence, automation, and accountability within the engineering team. - Manage the day-to-day project timelines, resource allocation, and operational activities to ensure successful platform delivery. - Implement and optimize the cloud budget (FinOps) for your domain, ensuring cost-effective scaling. Stakeholder & Client Engagement: - Act as the primary technical expert in project-level discussions with clients, providing detailed solutioning and estimation for new deals. - Collaborate closely with product management and service delivery teams to ensure the platform meets their requirements. Qualifications Required: - 12+ years of experience in platform engineering or DevOps, with at least 4 years in a leadership role directly managing engineering teams. - Deep, hands-on experience in designing and managing complex infrastructure on AWS, GCP, or Azure, including expertise with Kubernetes, serverless, and core cloud services. - Demonstrable, in-depth implementation experience with MLOps lifecycle tools and infrastructure for LLMs. - Strong proficiency with Terraform or CloudFormation. - Proven ability to lead, mentor, and scale a technical team, driving projects from conception to production. - Exceptional problem-solving skills in debugging and solving complex technical issues in a distributed systems environment. As the Director of AI Platform & MLOps, you will play a crucial role in leading a team of engineers to architect, scale, and manage the infrastructure supporting AI Training Data Services. Your responsibilities will include translating the long-term vision into a technical roadmap, designing and implementing MLOps frameworks, managing multi-cloud infrastructure, and ensuring high availability and security of the platform. Key Responsibilities: - Translate the long-term vision into an executable technical roadmap, making key architectural decisions for the platform. - Lead the hands-on design and implementation of MLOps/LLMOPs framework, including CI/CD for models, data/model versioning, automated workflows, and monitoring. - Engineer and manage a scalable, multi-cloud infrastructure (AWS/GCP/Azure) using Infrastructure as Code (IaC) principles (Terraform, CloudFormation). - Oversee the technical integration, scaling, and reliability of data annotation platforms and the GIG worker technology layer. - Drive SRE best practices to ensure high availability, performance, and security of the entire platform. Team & Operational Leadership: - Recruit, lead, mentor, and directly manage a team of Cloud, DevOps, MLOps, and Site Reliability Engineers. - Foster a culture of technical excellence, automation, and accountability within the engineering team. - Manage the day-to-day project timelines, resource allocation, and operational activities to ensure successful platform delivery. - Implement and optimize the cloud budget (FinOps) for your domain, ensuring cost-effective scaling. Stakeholder & Client Engagement: - Act as the primary technical expert in project-level discussions with clients, providing detailed solutioning and estimation for new deals. - Collaborate closely with product management and service delivery teams to ensure the platform meets their requirements. Qualifications Required: - 12+ years of experience in platform engineering or DevOps, with at least 4 years in a leadership role directly managing engineering teams. - Deep, hands-on experience in designing and managing complex infrastructure on AWS, GCP, or Azure, including expertise with Kubernetes, serverless, and core cloud services. - Demonstrable, in-depth implementation experience with MLOps lifecycle tools and infrastructure for LLMs. - Strong proficiency wit
