Top Tech Jobs & Startup Jobs in NYC, NY

Serve as a client-facing compensation partner advising senior leaders and HR on program design, market benchmarking, job pricing, review cycles, and global practices. Perform data-driven analysis, recommend competitive and fair solutions, design enterprise compensation programs, support recruiting and new hire offers, and deliver training and change management.

Lead high-visibility AI-focused design initiatives: define opportunities, own projects end-to-end, execute interaction and visual design, simplify complex workflows, shape design strategy, collaborate with Product and Engineering, influence stakeholders, and use generative AI for exploration and prototyping.

Lead strategy and architecture for the enterprise knowledge/context layer powering AI: set standards, control models, connector strategy, and federated operating models. Ensure content is AI-ready, permissions-aware, and measurable for retrieval and grounding. Partner with IT, Engineering, Legal, Privacy, and Security to define eligibility, sensitivity, and lifecycle policies and drive adoption across domains.

Own and operate the Workforce Planning operating system: manage planning cycles, governance, executive reporting, enablement, adoption, cross-functional coordination, and delivery tracking to ensure consistent, scalable workforce planning outcomes.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

Lead full‑stack design and delivery of customer-facing web experiences (Browse, Navigate, Preview). Own architecture, APIs, data models, rollouts, observability, on‑call readiness, and cross-team alignment, using approved AI-assisted workflows while ensuring technical quality and reliability.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead and scale Product Marketing operations: build operating models for messaging lifecycle, portfolio and roadmap visibility, PMM launch governance, cross-functional decision rights, templates, reporting, and AI/automation-enabled workflows to improve launch readiness and go-to-market execution.