Tachyon Technologies LLC
Product Manager- AI
Chicago, Illinois, USA · full-time, part-time, contract, third party
Sponsorship not specifiedDetected 44 days ago
Machine LearningLLMsRAGAgentic AIAI OrchestrationProduct ManagementProduct StrategyStakeholder ManagementResearchLeadershipCollaboration
About the role
- It is not a single application but a growing family of products conversational assistants, agentic workflows, knowledge and retrieval, content creation, and the shared skills and services that power them.
Responsibilities
- Product Strategy & Ownership Lead the full product lifecycle for your product discovery, definition, launch, and iteration.
- Own the roadmap across its components and features, and connect it to the platform's broader goals Conduct user and stakeholder research to surface the highest-value problems, and prioritize the features that solve them.
- Execution & Delivery Collaborate with Engineering to: o Prioritize the backlog and sequence investments o Drive latency, quality, and cost improvements for your product o Improve scalability, reliability, and observability Define success metrics and contribute to evaluation and monitoring, both offline and online, including usage and cost models for your product's AI workloads.
- Own documentation and standards for your product, aligned to platform conventions.
- Stakeholder Management Partner across Engineering, Design, Security & Compliance, fellow product managers, and the practitioner community.
Nice to have
- Experience with professional services / consulting delivery models.
- Hands-on familiarity with AI tooling and agent frameworks.
- Background designing for both practitioner and leadership audiences.
- Communicate trade-offs and translate fluently between technical teams and business stakeholders.
- Present your product's roadmap, progress, and impact to platform leadership.
- What You'll Bring Proven PM experience shipping technical or platform products
- experience with AI/ML or data intensive products strongly preferred.
- Working fluency in modern AI (LLMs, agents, RAG, evaluation) and the trade-offs between them.
Skills
- Fluency in modern AI and the instinct to reach for it matter here as much as classic product judgment.
- Translate ambiguous needs into clear requirements and a defensible delivery plan.
- Turn repeatable patterns from real delivery into reusable, scalable product capabilities.
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