Top Tech Jobs & Startup Jobs

Embed with recruiting teams to enable AI-assisted hiring: teach and codify recruiter-built LLM skills, provide technical support, build fast pilots and prototypes, create documentation and enablement programs, and collaborate with People Products and governance to productionize successful workflows.

Lead architecture, automation, and ecosystem integration for Treasury systems: design a treasury data foundation, evaluate/implement TMS or internal builds, automate cash and payment workflows (Claude-powered), ensure SOX-compliant controls, and partner across Treasury, Finance, Engineering, banks, and vendors. Manage roadmap, vendor relationships, and unblock one to two finance systems engineers while driving projects from design through production.

Lead design and implementation of Claude Science, partnering with researchers to turn model capabilities into production-grade scientific tooling. Shape product roadmap, ship 0→1 features, build evals, surface model failure modes, and collaborate with product, design, and research to accelerate scientific workflows across domains.

Own full-lifecycle recruiting for Infrastructure roles: run intakes, build pipelines of specialized talent, refine interview loops, advise hiring managers with market data, partner on offers, and handle confidential searches with discretion.

Lead customer storytelling for Industries: identify and prioritize verticals, develop referenceable customer stories, cultivate executive advocates, coordinate with Sales and Communications for announcements, and build scalable playbooks, processes, and creative campaigns to drive adoption of Claude.

The role involves owning the technical strategy for developer productivity, designing reliable distributed infrastructure, and leading complex developer infrastructure projects.

Design new information architectures for language models, refine their interaction with data, and develop evaluation sets to improve functionality.

Build and scale infrastructure and data pipelines for Safeguards ML research. Own training, evaluation, and scoring workflows, design researcher-facing tooling, ensure correctness and reliability, productionize high-value research workflows, and improve throughput, cost, and reliability of large-scale inference and scoring workloads while partnering with researchers.

As a Data Scientist in Marketing, you will enhance AI-driven marketing strategies, collaborate with teams to develop metrics, analyze marketing data, and recommend improvements for user engagement.

Provide commercial legal support for AI safety, research, and go-to-market agreements. Draft, review, and negotiate enterprise and research contracts, build contract templates and playbooks, partner with Sales, Policy, Safeguards, and Research teams, identify and escalate legal risks, and stay current on AI-related legal developments.