Tribe AI

HQ
New York
35 Total Employees
Year Founded: 2019

Jobs at Tribe AI

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Recently posted jobs

22 Days AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Own onboarding and offboarding, optimize Rippling and related HR systems, administer benefits and employment changes across US, Portugal, and Canada, and manage compliance, immigration, and work authorization processes. Support performance reviews, leveling, recognition, and other people programs while building scalable, AI-enabled workflows and documentation. Partner across teams and help expand manager support and HRBP capabilities as the company grows.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Own Tribe’s corporate security, compliance, AI governance, and client-facing security programs. Lead SOC 2 and future certification efforts, enterprise security reviews, risk management, security controls, incident response, vendor risk, and Trust Center operations. Establish governance for AI agents, assistants, model providers, and subprocessors while partnering with engineering on architecture reviews, threat modeling, secure SDLC, data flows, and production readiness. Translate customer requirements into scalable security controls and operating processes.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead design of AI agent experiences—conversation and voice flows, multi-turn dialogs, escalation and error handling. Create user journeys, information architecture, wireframes, and clickable prototypes. Co-facilitate discovery workshops, ground decisions in user research, contribute to design systems, and ensure scalable, production-ready UX patterns for enterprise AI deployments.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead client-facing AI engagements: design end-to-end AI/ML architectures, drive technical discovery, enable engineers, translate technical choices to business outcomes, and create reusable deployment patterns.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead technical discovery and architect end-to-end GenAI and ML systems. Build rapid prototypes, define production-grade architectures (security, observability, deployment), create reference architectures, advise stakeholders, partner with sales and delivery teams, and collaborate with OpenAI/Anthropic to validate approaches and unblock technical constraints.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead client-embedded product strategy and delivery for enterprise AI solutions (80% onsite). Drive solution discovery, define product vision, prioritize backlogs, prototype, and manage end-to-end implementation. Translate client work into scalable internal products, share best practices, and influence executive stakeholders to ensure value realization.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead client-facing AI engineering engagements: build and deploy production LLM systems using RAG, vector DBs, and agent frameworks; handle cloud deployments, CI/CD, and reliability; debug enterprise issues (auth, networking, data); embed with client teams and document solutions for reuse.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Lead and grow Tribe's strategic partnerships with frontier AI and cloud providers. Build partner GTM programs, drive co-sell and product alignment, surface joint customer narratives, track partner-influenced pipeline, and shape long-term partner strategy in a fast-moving GenAI ecosystem.
One Month AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning • Consulting
Own technical transformation for 1-2 enterprise clients as a field CTO: set technical direction, lead cross-functional teams, advise C-suite, and build reusable Tribe IP (architecture patterns, evaluation frameworks, deployment playbooks). Hire and develop teams, translate field lessons into practice, and ensure production-grade AI/ML systems that scale and deliver business outcomes.