Act as the commercial co-founder to define and execute the go-to-market strategy and build the revenue engine from the ground up. Lead enterprise sales cycles, engage with C-level security stakeholders, and establish the company's first major customer base.
Pragmatike
20 Remote Job Openings at Pragmatike
Maintain and support core bare-metal infrastructure and scalable networks using Linux and automation tools. Design and implement server discovery, OS deployment, and observability stacks for high-performance compute workloads.
Maintain and support core bare-metal infrastructure, focusing on Linux systems, hardware-level diagnostics, and scalable networking. Automate provisioning and operations using Ansible and Python while managing observability stacks and virtualization platforms.
Maintain and support core bare-metal infrastructure and scalable networks using Linux and automation tools. Design and implement server discovery, OS deployment, and observability stacks for high-performance compute workloads.
Maintain and automate large-scale bare-metal infrastructure using MAAS and Linux. Design scalable networks and implement observability stacks for monitoring and log centralization.
Maintain and automate large-scale bare-metal infrastructure using MAAS and Linux. Design scalable networks and implement observability stacks for monitoring and logging.
Maintain and support core bare-metal infrastructure and scalable networks using MAAS and Linux. Automate provisioning and observability stacks while integrating internal APIs for resource allocation.
Maintain and support core bare-metal infrastructure and scalable networks using MAAS and Linux. Automate provisioning and observability stacks while integrating internal APIs for resource allocation.
Maintain and support core bare-metal infrastructure and scalable networks using MAAS and Linux. Automate provisioning and operations while managing observability stacks and virtualization systems like OpenStack.
Maintain and support core bare-metal infrastructure and scalable networks using MAAS and Linux. Automate provisioning and observability stacks while integrating internal APIs for resource allocation.
Design, develop, and maintain scalable full-stack applications and backend services to improve user-facing experiences. Collaborate with cross-functional teams to define engineering standards and own projects from concept through deployment.
Fullstack Software Engineer (TypeScript) - US Remote
Pragmatike
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Full Time
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14 days ago
Pragmatike
Design, develop, and maintain scalable backend services and high-throughput workflows using TypeScript and NestJS. Collaborate with cross-functional teams to implement event-driven systems and improve platform reliability and observability.
Design and maintain scalable backend services and APIs using TypeScript and NestJS to process high-volume transactions. Collaborate with cross-functional teams to implement event-driven systems and improve platform reliability and observability.
Develop and maintain native Android applications while designing scalable mobile architectures. Collaborate with cross-functional teams to optimize application performance and implement new features.
Design, build, and maintain scalable cloud-native infrastructure and CI/CD pipelines to support mission-critical applications. Focus on platform reliability, observability, and automating infrastructure provisioning using Infrastructure-as-Code tools.
You will manage and optimize enterprise storage and backup platforms across distributed environments while ensuring system health and performance. Additionally, you will troubleshoot complex infrastructure issues and contribute to automation efforts to improve operational reliability.
Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs to maximize performance and throughput. Collaborate with AI systems and distributed teams to improve GPU efficiency and scalability for mission-critical AI applications.
You will design and operate production-grade model serving infrastructure to support scalable, low-latency AI applications. This role involves managing the full lifecycle of ML systems, including deployment pipelines, GPU optimization, and system observability.
You will design and operate scalable, production-grade model serving infrastructure for AI applications. This includes managing deployment pipelines, optimizing GPU utilization, and ensuring high availability for real-time inference systems.
You will build, deploy, and operate production infrastructure across AWS, GCP, and Azure to support large-scale AI systems. This includes managing Kubernetes clusters, cloud networking, and optimizing performance and reliability for distributed workloads.