Top Tech Jobs & Startup Jobs in NYC, NY

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

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.

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.

This role focuses on optimizing compute allocation decisions using data science methodologies to improve user outcomes and operational changes.

As a Data Scientist focused on policy, you'll analyze data to inform policy discussions, support partnerships, and measure impact on public perception. You'll collaborate cross-functionally to create clear evidence and frameworks for AI policy communications.

Drive the adoption of AI solutions by securing strategic deals with mid-market companies, enhancing their business processes and product offerings.

Lead structuring and execution of financings supporting Anthropic's compute infrastructure. Manage end-to-end financing workstreams, build financial models, engage counterparties, negotiate terms, and partner with compute, treasury, legal, and finance teams. Develop repeatable frameworks, maintain counterparty relationships, and support broader corporate finance and capital markets analysis. Represent the company in negotiations and prepare clear recommendations for finance leadership.

Lead cross-functional coordination for GTM systems initiatives (CPQ, deployment tracking, account data quality). Run quarterly business reviews, align stakeholders across Sales, CS, RevOps, Deal Desk and BizTech, translate between technical and executive priorities, define business outcomes and metrics, maintain program documentation, and surface and resolve risks and dependencies to drive programs to measurable outcomes.

Manage startup accounts, build engagement models, identify growth opportunities, develop best practices for customer engagement, and collaborate on technical needs.

The Engineering Manager will lead a team developing AI-powered cybersecurity products, managing hiring, technical direction, and product delivery while engaging with customers and researchers to drive product development.