Reducto
AI
InfrastructureEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Infrastructure Engineer at Reducto. Skills: Infrastructure architecture, Scalable systems for AI/ML workloads, Cloud infrastructure automation, Monitoring and incident response practices, Reliability engineering. Designing, building, and maintaining highly available, scalable infrastructure to support intensive AI/ML workloads and real-time model deployments. Implementing robust monitoring, alerting, and observability systems to ensure system health, performance, and uptime across cloud and on-p”
What You'll Achieve.
Set the standard for reliability; Ensure system health, performance, and uptime; Minimize downtime; Maintain world-class service levels for enterprise customers
Industry & Context.
Proactively identifying, investigating, and resolving incidents; Debugging, optimizing, and automating infrastructure; Diagnose, experiment, and address reliability problems
This is an in person role at our office in SF, The role requires working hard and moving quickly
What They're Looking For.
Must Have
5+ years of hands-on experience in building or supporting production-grade infrastructure and reliability processes for high-throughput systems, Comfortable with Python or similar languages, Exceptional at working across cloud platforms, container orchestration (e. g. , Kubernetes), networking, and storage technologies
Nice to Have
Prior experience founding a company or building products/infrastructure in early-stage, high-growth environments, Excited about automating incident management processes with LLMs/AI, Driven, ambitious, and deeply care about both technical excellence and collaborative problem-solving, Keep up with the latest trends in cloud, observability, and SRE best practices, Passionate about open-source and have contributed tools or automation to reliability communities, Built or optimized monitoring, incident response, or high-performance computing systems for demanding AI/ML, fintech, or enterprise clients
What You'll Do.
and maintaining highly available
scalable infrastructure to support intensive AI/ML workloads and real-time model deployments
Implementing robust monitoring
and observability systems to ensure system health
and uptime across cloud and on-prem environments
and automating infrastructure for fast iteration and rapid deployment cycles
focusing on both reliability and developer velocity
Proactively identifying
and resolving incidents to minimize downtime and maintain world-class service levels for enterprise customers
How You'll Work.
Team & Collaboration
Collaborating closely with engineers, ML specialists, and founders to shape product, infrastructure, and security strategies; Collaborative problem-solving
Full Job Description
About Reducto Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. We’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms. Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital. The Opportunity As an Infrastructure Engineer at Reducto, you will influence every aspect of our infrastructure from the ground up. You will architect and scale resilient systems for AI and ML workloads, automate cloud infrastructure, and implement monitoring and incident response practices that set the standard for reliability. This role requires technical leadership, hands-on systems engineering, and strong collaboration with our founders and product teams as we build a company around reliability, rapid iteration, and high-impact product delivery. THE CORE WORK WILL INCLUDE: - Designing, building, and maintaining highly available, scalable infrastructure to support intensive AI/ML workloads and real-time model deployments. - Implementing robust monitoring, alerting, and observability systems to ensure system health, performance, and uptime across cloud and on-prem environments. - Debugging, optimizing, and automating infrastructure for fast iteration and rapid deployment cycles, focusing on both reliability and developer velocity. - Proactively identifying, investigating, and resolving incidents to minimize downtime and maintain world-class service levels for enterprise customers. - Collaborating closely with engineers, ML specialists, and founders to shape product, infrastructure, and security strategies. WE WOULD LOVE TO MEET YOU IF YOU: -
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