Role Description The Windows Server Automation engineer utilizes their automation skills and DevOps skills to build solutions for windows server customers and operations teams. Using automation tools, they ensure windows servers stay compliant across the fleet, and are kept secure with maximum server uptime and stability. - Automate the creation and testing of Windows Server templates for virtual machines and physical hardware using a CI/CD pipeline. - Automate the installation and configuration of Windows Server Operating System infrastructure using a multitude of tools such as Terraform, vRA/vRO, Habitat, Chef, Ruby, PowerShell. - Automate manual processes associated with infrastructure deployment via pipelines and infrastructure-as-code. - Provide cross-team support for deploying Windows Server infrastructure to multiple target environments. - Provide technical direction for the Windows Server Operating System platform. - Review and evaluate monthly Windows Security updates for Microsoft Server Operating system and determine a criticality level for each update based on mitigating and environmental factors. Engineer deployment process for High and Critically rated security updates. - Change management. Qualifications - Bachelor's degree or equivalent work experience. - Deep technical knowledge of Windows Server Operating Systems (2012R2/2016/2019). - Deep technical knowledge of Windows PowerShell. - Technical knowledge of Windows Internet Information Services (IIS). - Technical knowledge of Windows Clustering. - 5+ years of demonstrated ability with Microsoft Windows Server OS and related technologies. - 5+ years of experience with Windows Server Operating system for virtual machines and physical hardware. - Experience with VMWare and HPE server technologies. - Experience with scripting and programming languages with a focus on PowerShell (PowerShell, Batch, Ruby, Groovy, etc). Requirements - Operations experience supporting Windows Servers for a large enterprise. - Operations experience supporting IIS and Windows Clustering for a large enterprise. - Experience engineering the deployment of Windows Server Operating System for a large enterprise. - Experience with the following software a plus: Chef, Habitat, Terraform, Jenkins, Ruby, GitHub. - Experience supporting AV/Anti-Malware products for Windows Server Operating System. - Experience working in a DevOps environment. - Code first mentality. - Fundamental understanding of modern platform technologies and industry standard methodologies. - Technical certifications e.g. MCSA, MCSE, MCP, etc. - Agile/Lean methodologies experience. - Provides guidance in the design, integration and maintenance of the technical infrastructure and services (all aspects of the technology lifecycle) for the Windows Server Operating System. Benefits - Immediate medical, dental, vision and prescription drug coverage. - Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more. - Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more. - Vehicle discount program for employees and family members and management leases. - Tuition assistance. - Established and active employee resource groups. - Paid time off for individual and team community service. - A generous schedule of paid holidays, including the week between Christmas and New Year’s Day. - Paid time off and the option to purchase additional vacation time.

• Automate the creation and testing of Windows Server templates for virtual machines and physical hardware using a CI/CD pipeline • Automate the installation and configuration of Windows Server Operating System infrastructure using a multitude of tools such as Terraform, vRA/vRO, Habitat, Chef, Ruby, PowerShell • Automate manual processes associated with infrastructure deployment via pipelines and infrastructure-as-code • Provide cross-team support for deploying Windows Server infrastructure to multiple target environments • Provide technical direction for the Windows Server Operating System platform • Review and evaluate monthly Windows Security updates for Microsoft Server Operating system and determine a criticality level for each update based on mitigating and environmental factors. Engineer deployment process for High and Critically rated security updates • Change management

• Lead the end-to-end design and delivery of scalable, secure, and intelligent data products and AI automation solutions that support HackerOne's transformation into an AI-first organization. • Build, optimize, and maintain data pipelines and infrastructure that serve as the foundation for AI-powered systems and agentic operations. • Design and deploy AI-powered automation solutions that eliminate routine, manual work and unlock human capacity for strategic direction, creativity, and edge-case governance. • Partner across business and engineering teams to identify high-leverage opportunities for automation, integration, and system modernization. • Drive the architecture and execution of platform-level capabilities, leveraging AI and modern tooling to reduce manual effort, improve decision-making, and increase system resilience. • Provide technical leadership to internal engineers and external development partners, ensuring design quality, operational excellence, and long-term maintainability. • Shape and contribute to our incident and on-call response strategy, playbooks, and processes, focusing on building systems that fail gracefully and recover quickly. • Act as a multiplier to mentor other engineers, advocate for technical excellence, and promote a culture of innovation, curiosity, and continuous improvement. • Champion effective change management and enablement, ensuring systems are not only launched, but adopted, understood, and evolved.

• Design and operate AI-powered pipelines that transform data acquisition, enrichment, and validation. • Partner with Data Engineering and Operations to move pipelines from prototype to production. • Design, develop, and evaluate machine learning models for data enrichment and validation. • Implement OCR, NLP, and layout recognition pipelines for data extraction. • Build Python-based microservices for document classification and metadata extraction. • Integrate LLM APIs for intelligent extraction and task classification. • Monitor and optimize model performance tracking. • Design and implement conversational AI solutions with Amazon Connect and Amazon Lex. • Build automated calling workflows for project updates from contractors. • Ensure compliance with regulations for outbound communications. • Collaborate with Data Engineers to ensure seamless ML pipeline integration with data warehouses.