Architect and scale enterprise-grade GenAI and Agentic AI solutions, including orchestration, RAG, tool use, memory, evaluation, safety and human oversight.
Integrate the digital stack. Connect models and AI services with enterprise platforms, data sources, workflow systems, user interfaces and upstream or downstream applications.
Infrastructure & Engineering Excellence: Manage infrastructure and CI/CD pipelines while ensuring scalability, performance, security, and high code quality through best practices and governance.
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
Technical Leadership. Define the technical roadmap and reference architectures for AI Engineering. Serve primary technical authority on design reviews, build-vs-buy decisions and technology adoption.