创始人工智能原生 TPM 与系统完整性负责人
Founding AI-Native TPM & Systems Integrity Lead
为什么这个职位存在
在人工智能时代,执行方式正在被根本性地重新设计。
以前需要:
- 手动指定
- 手动测试
- 手动协调
的工作正变得越来越多地由AI操作和代理驱动。
这改变了技术项目管理和质量保证的角色。
不再管理任务和报告缺陷,系统本身可以:
- 生成规范
- 模拟工作流程
- 验证结果
关键的是:
有人能够设计这个系统如何运作,并确保它产生正确的结果。
这个职位的职责
这个职位结合了:
- 技术项目管理(TPM)——团队对齐、协调、KPI、成果
- 质量保证(QA)——系统正确性、验证、可复现性
为AI原生系统而重新设计。
你负责:
- 系统中工作的执行方式
- 系统在现实条件下的行为是否正确
问题
年轻人比以往任何时候都更加在线连接,但比任何一代人都更感到孤独。
大多数数字平台都优化为屏幕上的被动消费,让人们远离他们所处的环境。
我们正在探索相反的方向:
一种将人们带入现实环境的技术。
要做到这一点,软件必须理解地点、上下文和协调行动,而不仅仅是用户和点击。
我们正在构建什么
Vyry是基础设施,允许物理场所通过人类参与积累持久的数字意义。
当学生协作完成任务时,他们不仅仅是在完成活动。他们正在创造与真实地点相关的艺术品、关系和身份痕迹。
随着时间推移,校园会发展出一个持久的体验层,其中地点包含由社区自己生成的记忆、共同创作的资产和发现路径。
这些体验不是产品。
它们是系统学习人类如何在物理环境中协调和共同创造意义的行为界面。
Phygtl正在构建一个系统,其中:
- 物理环境成为有状态的系统
- 人类协调生成持久的产物
- 地点积累结构化的记忆和身份
- 分布式服务维护这些环境的世界状态
近期成果
- 2025年从1.2万增加到17.5万名学生
- 25%的MAU完成任务
- 试点项目显示社交孤立减少高达40%
团队结合了消费者产品、空间和游戏世界的专业知识,拥有经验丰富的人才
查看英文原文
Why This Role Exists
In the age of AI, execution is being fundamentally redesigned.
Work that was previously:
- manually specified
- manually tested
- manually coordinated
is increasingly becoming AI-operated and agent-driven.
This changes the role of Technical Project Management and QA.
Instead of managing tasks and reporting bugs, the system itself can:
- generate specifications
- simulate workflows
- validate outcomes
What becomes critical is:
someone who designs how this system operates and ensures it produces correct outcomes.
What This Role Is
This role combines:
- Technical Project Management (TPM) — team alignment, orchestration, KPIs, outcomes
- Quality Assurance (QA) — system correctness, validation, reproducibility
Redesigned for an AI-native system.
You own:
- how work is executed across the system
- whether the system behaves correctly under real-world conditions
The Problem
Young people are more connected online than ever, yet lonelier than any generation before them.
Most digital platforms are optimized for passive consumption on screens, pulling people away from the environments they live in.
We are exploring the opposite:
technology that brings people together in real-world environments.
To do that, software must understand place, context, and coordinated action, not just users and clicks.
What We Are Building
Vyry is infrastructure that allows physical places to accumulate persistent digital meaning through human participation.
When students coordinate in quests, they are not simply completing activities. They are creating artifacts, relationships, and identity traces that remain anchored to real locations.
Over time, campuses develop a persistent experiential layer, where places contain memories, co-created assets, and discovery paths generated by the community itself.
The experiences are not the product.
They are the behavioral interface through which the system learns how humans coordinate and co-create meaning in physical environments.
Phygtl is building a system where:
- physical environments become stateful systems
- human coordination generates persistent artifacts
- places accumulate structured memory and identity
- distributed services maintain the world state of these environments
Recent proofs
- 12k → 175k students reached in 2025
- 25% of MAUs complete quests
- pilots show up to 40% reduction in social isolation
The team combines consumer product, spatial, and game-world expertise, with seasoned talent from:
Roblox • Niantic • Ubisoft
alongside a research layer that includes:
2 professors • 4 PhDs
Future Direction
Today Vyry operates as a mobile app.
The next phase evolves the system into infrastructure for smart glasses.
The long-term architecture enables developers and brands to create context-aware activities inside the spatial environment, similar to how platforms like Roblox enabled creators to build experiences on top of a shared world layer.
This requires building systems that not only scale technically, but behave correctly under real-world coordination.
What You Will Do
You operate across three layers:
1. Execution Layer (TPM)
You ensure work flows correctly across the system:
- align teams around clear outcomes
- orchestrate execution across product, engineering, and AI systems
- translate system needs into structured work (Jira or equivalent)
- define KPIs such as:
- system correctness
- time to resolution
- execution quality
- ensure outcomes match expectations
2. Correctness Layer (QA)
You ensure the system behaves correctly (Agents to run QA for Unity):
- define expected system behavior across flows
- identify where behavior diverges
- reproduce issues and edge cases
- validate fixes
- ensure failures are:
- understood at root cause
- reproducible
- prevented from recurring
3. AI-Native Layer
You design how validation and execution scale:
- implement agents that:
- simulate user behavior
- test flows
- validate outcomes
- measure system performance
- create feedback loops that continuously improve the system
- reduce reliance on manual QA and manual coordination
Operational Ownership
You will define how system behavior becomes actionable across the team.
This includes:
- translating system gaps into clear, structured tasks (tickets, flows, validation units)
- ensuring issues are:
- clearly defined
- reproducible
- outcome-driven
- establishing and evolving KPIs, including:
- system correctness
- validation coverage
- time to resolution
- owning how work is tracked and resolved (Jira or equivalent)
- ensuring bugs are not just reported, but:
- fully understood
- fixed at the root
- prevented from recurring
Hard Problems We’re Exploring
- ensuring correctness across multi-user, multi-step coordination flows
- designing validation systems that scale with real-world complexity
- orchestrating AI agents to simulate and validate system behavior
- building systems that detect and resolve failures before users experience them
Role
We are looking for a founding-level system operator and builder.
This role sits at the intersection of:
- execution (TPM)
- correctness (QA)
- automation (AI)
This is not a traditional TPM role.
This is not a manual QA role.
This is ownership of a new system layer.
Without this role, the system scales in features but not in correctness, and breaks under real-world coordination.
Compensation
This is an equity-first founding role.
Compensation is equity-only until our next funding round (target H2 2026).
You can join either:
- Part-time, while keeping your current role
- Full-time
This role is designed for someone who wants to be a founding member without starting from scratch alone.
Who This Is For
People who:
- think in systems and execution, not just features
- are strong in:
- team alignment
- orchestration
- driving outcomes
- naturally identify:
- edge cases
- system failures
- are comfortable working with:
- engineers
- AI systems
- product flows
- care deeply about correctness and outcomes
Who This Is NOT For
Please do not apply if:
- you are looking for a salaried job today
- you want a freelance contract or short-term gig
- you are bridging time until your next role
- you prefer clearly defined specs over ambiguous systems
This is a founding role with real ownership and ambiguity.
If Interested
Send:
- a short note on why this role resonates
- examples of systems you’ve debugged, validated, or improved
Final Thought
If you have thought, “I want to build my own startup and make a real impact” — and are looking to do it as part of a team already in motion — we want to hear form you
Originally posted on Himalayas