Top Tech Jobs & Startup Jobs in Seattle, WA

Own strategic partnerships with major technology companies, managing relationship strategy, product integrations, distribution, infrastructure, and complex commercial agreements. Lead multiple negotiations, structure novel multi-year deals, engage senior executives, and coordinate Product, Engineering, Sales, Marketing, Finance, Legal, and Policy through execution. Provide strategic judgment on high-stakes trade-offs and ensure signed agreements can be delivered.

Lead Anthropic’s global equity administration and payroll operations, including strategy, controls, systems architecture, international expansion, compliance, automation, accounting partnerships, and public-company readiness. Manage senior functional leaders and collaborate with Legal, Tax, HR, Accounting, and external providers. Build scalable processes, oversee cross-border payroll and equity programs, support stock-based compensation reporting and audits, and develop headcount and resourcing plans.

Design, build, and operate high-scale sandboxing infrastructure for untrusted AI-generated code and agent workloads. Responsibilities include improving startup speed and resource density, strengthening compute, filesystem, and network isolation, debugging kernel and virtualization issues, developing observability tools, supporting reinforcement learning environments, and hardening systems against escape scenarios. The role partners with research, product, platform, security, and cloud teams to deliver reliable, secure sandbox capabilities.

Design, build, and operate distributed systems supporting reinforcement learning at frontier scale. Responsibilities include scheduling, data movement, storage, networking, fault tolerance, autoscaling, observability, automation, and performance optimization across large accelerator fleets. The role requires debugging complex distributed failures, preserving training correctness, collaborating with researchers, and creating resilient systems that continue operating through hardware failures and changing workloads.

Develops reinforcement learning algorithms, model architectures, and experimental infrastructure for frontier-scale training. Responsibilities include scaling RL across model size, context length, and compute; diagnosing numerical, algorithmic, and systemic failures; optimizing performance and cost; and managing end-to-end large-scale runs. The role requires rigorous experimentation, distributed training expertise, quantitative modeling, and strong programming across the ML systems stack.

Build and operate secure, reliable cloud infrastructure, storage systems, and data pipelines for specialized legal and privacy workloads. Translate legal, privacy, and security requirements into scalable, auditable architectures; manage chain of custody and data integrity; partner with Legal, Privacy, Security, Research, and Infrastructure teams; and deliver production systems under fixed deadlines. The role also requires advising nontechnical stakeholders and extending shared infrastructure for novel legal requests.

Design and ship polished product experiences for Anthropic’s Claude Developer Platform. Collaborate with product managers, engineers, and AI researchers to define product vision, workflows, primitives, and roadmaps. Create high-quality interfaces, prototypes, and designs for complex developer tools and AI capabilities while understanding technical architecture. Work quickly in an ambiguous startup environment, using code and AI tools to prototype, iterate, and improve user trust, consistency, and overall product quality.

Build and operate cloud inference launch infrastructure for Claude across AWS, GCP, Azure, and future providers. Develop validation pipelines, CI/CD systems, performance benchmarks, shadow traffic testing, correctness checks, and observability. Integrate new model architectures and inference features, resolve cross-cloud reliability and performance issues, optimize accelerator usage, and reduce deployment cycle times. Collaborate with inference teams and cloud partners while owning large-scale distributed systems and automation end to end.

Designs and operates large-scale distributed inference systems serving Claude globally. Responsibilities include intelligent routing, load balancing, traffic management, autoscaling, cloud orchestration, deployment pipelines, model serving, accelerator integration, observability, and performance optimization across multiple regions and cloud providers.

Design and operate backend services and infrastructure for Claude inference across AWS, GCP, Azure, and future cloud platforms. Build CI/CD deployment pipelines, multi-cloud abstractions, capacity and autoscaling systems, workload routing, and observability tooling. Collaborate with internal engineering and security teams and external cloud providers to launch reliable, cost-effective model-serving capabilities at massive scale. Analyze production performance, cost, and reliability issues and drive remediation.