About the Role
0G is building the platform that enables AI agents to complete complex, long-running tasks. We're looking for a Product Manager to own the 0G Agent Harness, agent memory, tooling, evals and developer APIs.
Your focus will be making agents fast, reliable and capable - from accessing tools and retaining useful context to completing tasks with minimal intervention. You'll work closely with engineering to understand developer needs, define priorities and use evaluation results to guide product decisions.
This role suits someone who has built LLM platforms, API products, search and retrieval systems or developer tools. You may have started as an engineer; what matters is your ability to combine technical depth with strong product judgment.
Key Responsibilities
Own the Agent Platform roadmap
- Define the product direction, requirements and priorities for the 0G Agent Harness.
- Understand developer use cases and translate them into platform capabilities, clear specifications and measurable outcomes.
- Make trade-offs across capability, reliability, latency, cost and developer experience.
Build capabilities for complex, long-running tasks
- Own the product roadmap for agent memory and tooling, including browser access, sandbox environments, tool calling and payment modules.
- Identify where agents lose context, misuse tools, stall or fail to complete tasks, and prioritise improvements with engineering.
- Define expected behaviour, failure handling and acceptance criteria for new capabilities.
Make product decisions from evals
- Partner with engineering to develop evaluations grounded in real user tasks.
- Establish measures for task completion, output quality, latency and reliability.
- Use eval results, production feedback and failure analysis to guide releases, identify regressions and prioritise the roadmap.
Create a strong developer experience
- Shape developer APIs and workflows that make the platform straightforward to integrate, test and troubleshoot.
- Work with developers to understand adoption barriers and turn feedback into product improvements.
- Partner with engineering and technical content teams on documentation, examples and release communication.
Drive delivery and learning
- Align engineering and other stakeholders around clear priorities and release goals.
- Stay involved from discovery through launch, assess results and refine the roadmap based on evidence.
What You'll Bring
- Experience owning products in LLM platforms, APIs, developer tools, search and retrieval, or related technical infrastructure.
- Enough technical depth to discuss APIs, system behaviour and engineering trade-offs with confidence.
- A track record of turning ambiguous customer needs into clear product requirements and shipped capabilities.
- Experience using evaluations, experiments or performance data to make product decisions.
- Strong judgment about which problems to solve first and how to balance near-term delivery with platform development.
- Clear communication and the ability to build alignment across technical and business teams.
Preferred / Nice-to-Have Qualifications
- Previous experience as a software engineer or another hands-on technical practitioner.
- Experience with agent frameworks, memory systems, retrieval, tool execution or sandboxed environments.
- Experience building eval suites or improving the reliability of AI systems in production.
- Familiarity with developer communities, open-source products or API ecosystems.
What to Share
Alongside your résumé, tell us about a technical product you owned: the users and problem, the decisions you made, how you measured success and what changed after launch. We're particularly interested in examples where evaluation results or failure analysis changed your product priorities.
Perks & Compensation
- Purpose: The opportunity to contribute to making AI a public good
- Growth: A self-directed environment where you can take initiative to shape your role and career
- Compensation: Market-competitive compensation including, for most roles, exposure to pre-launch tokens
In addition, 0G Labs is committed to the health and well being of all of our team members. To that end, we provide reimbursements towards a holistic set of experiences and courses:
- Core self: Transcendental Meditation
- Mind: Landmark Education
- Emotion: Art of Communication
- Presence: Speech Coach
- Body: Fitness, gym and exercise memberships/classes
About 0G Labs
0G Labs, founded in 2023 by Michael Heinrich, Ming Wu, Fan Long and Thomas Yao in San Francisco, builds 0G, a modular decentralized AI chain designed as an operating system for AI. Its stack combines a high-throughput data availability and storage layer with compute and serving infrastructure, including 0G Storage, 0G DA and 0G Serving for inference and model orchestration. The architecture targets verifiable AI workflows, on-chain model deployment and data provenance without centralized intermediaries. Backed by leading investors and incubated with research partners across Web3 and AI, 0G is building toward mainnet with testnet participation and ecosystem grants. Headquartered in San Francisco with a distributed research and engineering team and Cayman foundation presence, 0G sits at the intersection of cryptography and machine learning. Expect a research-driven culture that values systems engineering, AI openness and shipping performant infrastructure for decentralized intelligence.