Strategic Projects Lead at Chakra Labs | NY, US | Rezi

Strategic Projects Lead at Chakra Labs

Strategic Projects Lead

Chakra Labs · NY, US

Today

Strategic Projects Lead

Chakra Labs · NY, US

19 hours ago
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About the Role

The Strategic Projects Lead owns customer projects end-to-end, transforming vague research goals into trusted datasets. This role is operationally intense, requiring deep understanding of specifications, stakeholder management, and high-quality deliverable fulfillment.

Responsibilities

  • Own multi-project delivery end to end, including scoping, contributor orchestration, quality assessment, and shipping.
  • Recruit and manage a pool of expert contributors who build gyms and trajectories.
  • Track and prioritize milestones for project completion in a dynamic requirements environment.
  • Assess delivery quality regularly before customer submission.

Requirements

  • Operationally intense background (Consulting, banking, private equity, startup operations, ex-founder, or human-data industry).
  • Approximately 2+ years of experience, with flexibility for strong candidates.
  • Proven experience in creating positive customer outcomes under deadline pressure.
  • Ability to lead through influence, managing expert contributors without direct authority.
  • Capacity to develop clear specifications, build credibility, and ensure follow-through.
  • Ability to think quickly, set priorities, and make decisions impacting business outcomes.
  • Willingness to partner directly with researchers to understand model failures and market dynamics.
  • Desire to stay close to the cutting edge of frontier model research.

Skills

  • Specification understanding
  • Stakeholder management
  • Project delivery
  • Contributor management
  • Quality assessment
  • Strategic thinking
  • Product management
  • Influence leadership
  • Rapid decision-making

Experience Level

  • 2+ years

About the Company

  • Chakra Labs' mission is to encode human taste into intelligence.
  • We build high-fidelity environments, evals, and datasets for frontier AI research.
  • Our work focuses on post-training, agent environments, data quality, and research infrastructure.
  • We aim to build measurable, useful, and hard-to-fake AI model improvements.