Senior Network & Site Reliability Engineer (San Francisco)

About UsAlembic is the pioneering Causal AI platform. We help the world's largest enterprises move past correlation to prove what actually drives business outcomes — the question marketing and growth teams have never been able to answer with confidence. Fortune 100 companies including Nvidia, Delta Air Lines, and Mars use Alembic to make multimillion-dollar decisions on trusted, causal evidence.We're backed by a $145M Series B from WndrCo (founded by Jeffrey Katzenberg), Jensen Huang, Joe Montana, Prysm Capital, and Accenture. Our models run on our own NVIDIA DGX SuperPOD built on Grace Blackwell infrastructure — one of the fastest private supercomputers in the world. (We've melted GPUs getting here.)About the RoleWe're building infrastructure that has to perform under real-world scale, reliability, and security demands — and we're looking for an engineer who wants to own the foundation it runs on. This isn't a traditional keep the lights on role.You'll design and operate the global network and reliability layer behind one of the world's fastest private supercomputers — the fabric powering distributed compute, ML workloads, real-time analytics, and mission-critical enterprise systems. You'll work across networking, systems, automation, observability, and reliability engineering to scale a platform where performance genuinely matters, with real influence over architecture decisions.It's a strong fit if you like solving deep infrastructure problems, building resilient systems, automating everything repetitive, and owning architecture rather than just maintaining it.What You'll DoArchitect and operate scalable, secure network architecture for high-security requirements and large-scale machine learning workloads.Own network device configuration management end to end, ensuring consistency and reliability across the fleet.Improve system and network reliability and performance through automation, observability, and proactive capacity planning.Implement and manage complex network protocols and connectivity, including BGP, VPNs, and WAN circuits and external peering.Build and maintain comprehensive monitoring, alerting, and incident response — SLOs, runbooks, and on-call rotations — and drive post-incident analysis and continuous improvement.Ensure security, compliance, and operational readiness across our network and cloud infrastructure.Partner across engineering and data science to drive a culture of performance and reliability.What Will Help You Succeed8+ years in network or infrastructure engineering, including 5+ years in datacenter operations and/or systems and network administration.A strong background in network security, architecture, design, and operations.Extensive hands-on experience with network devices (firewalls, switches, load balancers) and large-scale architectures and protocols — BGP, QoS, MPLS, and IPsec VPNs.Experience designing and operating modern datacenter network fabrics (spine-leaf, EVPN/VXLAN, ECMP).Network automation and IaC tooling (Ansible, Terraform, Nornir, or similar), plus IPAM/DCIM platforms (NetBox, Infoblox, or similar).WAN engineering — carrier circuit provisioning and external network peering.Familiarity with Kubernetes networking (CNI plugins, ingress, service networking, network policy) and strong operational experience with Linux-based production infrastructure.Experience with monitoring and observability stacks (Prometheus, Grafana, Datadog, ELK, OpenTelemetry).Solid scripting (Python, Bash) to debug complex network and system issues and automate solutions, plus excellent cross-functional communication.Also HelpfulNVIDIA networking technologies — Cumulus Linux, InfiniBand, Spectrum-X, and BlueField DPUs (this is the fabric behind our SuperPOD).Familiarity with data-intensive platforms (Spark, Airflow, Kafka) and storage network protocols (NFS, LustreFS, iSCSI).Security practices for applications and infrastructure, and experience in high-compliance or SOC 2 environments.The Role Is Right for You IfYou want to own mission-critical network and infrastructure end to end — from architecture to incident management — not just keep it running.You'd rather build and automate than direct from a distance, and you want meaningful influence over how a high-performance platform scales.Why You Might Be Excited About AlembicHard problems with real impact: You'll own the network and reliability layer behind systems that influence multimillion-dollar decisions at Fortune 100 companies.Cutting-edge technology: Operate our own NVIDIA DGX SuperPOD on Grace Blackwell — one of the fastest private supercomputers in the world — and run a fabric (InfiniBand, Spectrum-X, BlueField) almost no company has in-house.Technical autonomy: Ownership over architecture decisions and the freedom to solve hard infrastructure problems your way.Elite team: Join top engineers who thrive on hard problems and high-impact work.Series B momentum, real ownership: Meaningful equity at a Series B company that's raised $145M, with proven product-market fit and Fortune 100 traction.Why You Might Not Be ExcitedIf you only want to tell people what to build instead of building and automating alongside them, this isn't the environment for you.You prefer companies with 100% built-out process for every detail.You prefer static over dynamic — projects and priorities adapt as we grow. We have real paying customers and a playbook, and we still move at startup speed at Series B scale.Compensation Range: $210K - $240KLocationSan Francisco HQAddressSan Francisco, CaliforniaEmployment TypeFull timeLocation TypeOn-siteDepartmentEngineeringTechnical OperationsCompensationOur compensation philosophy ensures new hires earn 50%+ current benchmarks. We'll discuss further with you. Most recent San Francisco benchmark data: $210K – $240KOur Compensation Philosophy:Market-based: Our formula ensures new hires earn at or above real-time benchmarks. Ownership: Our generous equity program ensures new hires are owners, not just employees.Transparent: We openly discuss salary expectations to avoid surprises later in the process. Data-driven: We use objective data to remove bias and ensure consistency in compensation decisions.