• Bridge the gap between research and real-world application. • Ensure high-performance infrastructure, automated pipelines, and deployment strategies. • Design and maintain scalable cloud environments (GCP/AWS) using Terraform. • Manage GPU/TPU resource allocation for training, fine-tuning, and interactive notebooks. • Build internal services and CLI tools for the AI team. • Design CI/CD and training pipelines using tools such as GitHub Actions, MLFlow, Vertex AI Pipelines. • Develop reusable patterns for model serving and manage service deployments to Kubernetes. • Manage and optimize vector databases and embedding pipelines for RAG-based systems. • Implement techniques to reduce latency and increase throughput.

• Design and build internal AI frameworks, SDKs, and shared libraries • Enable teams to integrate AI features with minimal friction • Set up standardized patterns for using LLMs, embeddings, agents, and workflows • Build reusable components for prompt management, evaluation, observability, and safety • Define best practices for AI usage, cost control, and reliability • Evangelise AI internally through documentation, examples, and hands-on guidance • Rapidly prototype AI-powered features and turn them into reusable building blocks • Own AI tooling from experimentation to production

• Infrastructure Management: Own and improve our multi-cloud infrastructure spread across AWS, GCP, and Digital Ocean. You will manage Kubernetes clusters, handle patching, manage access, and enhance to ensure our tooling has robust alerts and metrics. • CI/CD Optimization: Drive the improvement of GitHub CI pipelines. You will be responsible for creating secure, repeatable testing environments and automating pipeline updates to streamline the developer experience. • Internal Services Architecture: Architect and host infrastructure for engineering development, including internal services and vCluster-specific platforms (e.g., loft.rocks, vCluster Cloud). You will empower engineers to build pipelines securely through education and tooling. • Customer Zero: Act as the first and most critical user of our products. You will push vCluster features to their limits to create useful internal tools, discovering bugs and providing feedback to Engineering to shape the future of our software. • Terraform Automation: Focus on automating updates and managing infrastructure as code using Terraform Spacelift. You will give the team the ability to create infrastructure on demand, ensuring scalability and consistency. • Execution: Manage a variety of Kanban tasks via Linear, ranging from improving observability to handling GitHub policy requests, release engineering, and access management.

• Implement highly scalable, secure, resilient cloud-native and on-premise application platforms that host vulnerable applications, configurations, and other services vital to research and development of our product. • Identify, design, and implement improvements in deployment processes so engineers can begin development anytime with confidence. • Design and implement tooling for the internal platform to collect telemetry data used to gauge its effectiveness in supporting H3's engineers. • Help create an effective documentation culture within the Engineering Organization (Confluence, Documentation as code). • Participate in effective project management and work allocation (Jira, Agile Concepts). • Create Terraform modules and Ansible playbooks that are extensible across the infrastructure to reliably and effectively deploy vulnerable testing scenarios for engineering development efforts. • Be a positive example of automation for infrastructure-as-code, platform operations, and overall CI/CD methodologies. • Evaluate new technologies and patterns for automation, application hosting, and improving infrastructure provisioning. Recommend and define the work needed.