Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Own day-to-day product work across AI infrastructure (GPU clusters, managed storage, observability). Identify and drive resolution of hidden problems, run hypothesis-driven experiments, instrument data collection, and partner with engineering and cross-functional teams. Ramp to full ownership of an area (observability or storage) within months.

Lead and build the technical accounting function: set U.S. GAAP policies (ASC 606, 842, 360, 470/835, 805, 718, 505, 808), advise on complex transactions, manage investor reporting and annual audits, establish SOX/internal controls readiness, and drive scalable processes, close support, and cross-functional accounting partnerships in a high-growth AI infrastructure environment.

Design and implement manifest-driven provisioning and reconciliation systems for GPU hosts and clusters. Build durable workflow engines, declarative self-service APIs, event-driven automation, self-healing pipelines, and production-grade control planes. Own coding, testing, CI/CD, and operate the platform in production to eliminate manual provisioning.

As a Senior Developer Productivity Engineer, you will enhance CI/CD processes, optimize workflows, and build tools for efficient software delivery.

Provide legal support for infrastructure procurement and enterprise commercial deals. Lead negotiations for GPU/cloud capacity, data center, networking, and vendor agreements; align vendor terms with customer contracts; manage export controls and data/privacy compliance; build templates, playbooks, and scalable procurement and sales workflows; support partnerships, reseller and go-to-market deals; and run procurement processes and vendor template libraries.

Design and implement a scalable observability platform (metrics, logs, traces) using Prometheus, Grafana, ClickHouse/ClickStack, and OpenTelemetry. Build telemetry pipelines, automated monitoring, SLIs/SLOs, alerting, anomaly detection, and runbooks. Develop IaC and custom tools with Go, Python, Terraform, Ansible, and Helm. Collaborate on distributed tracing, lead incident response, and define observability best practices.

Design, deploy, and maintain large-scale hybrid data center networks; troubleshoot and analyze network issues; develop automation and tooling; evaluate and recommend hardware/software; manage vendor relationships; ensure reliability, scalability, and compliance; lead complex network projects and contribute to architecture and roadmaps.

The Manager will analyze and benchmark compute infrastructure sourcing and operations, driving strategic decisions and optimizing resource allocation across sites and vendors.

As an AI Infrastructure Engineer, you will manage user-facing services, ensure system reliability, and improve infrastructure using automation tools such as Ansible and Terraform while collaborating with various stakeholders.