资深应用AI工程师
Staff Applied AI Engineer
🚀 关于我们
我们是 StackBlitz 旗下的 Bolt.new!
我们带来了 WebContainers，这项开创性的技术使您可以在浏览器中直接运行 Node.js。这一突破开启了我们的旅程，自 2019 年以来，它支撑着每月超过 100 万开发者使用的极速在线 IDE。
但我们并未止步。
我们深入研究了所学到的一切，并构建了从想法到生产最快的方式，无需编写传统代码。这是一个下一代、由 AI 驱动的应用程序构建器，可帮助您在浏览器中立即创建、编辑和部署全栈网页和移动应用。无需安装。无需设置。只需智能自动化和即时开发环境，让您以思维的速度前进。
我们是一个完全远程的团队，全球分布，深度协作，对构建软件开发的未来充满热情。
这是您加入一个拥有远大愿景的小团队的机会。如果您热爱快速交付、解决真实问题并推动可能的边界，我们期待与您见面。
✨ 关于这个机会
作为 AI 团队的高级工程师，您将领导将自然语言转化为生产就绪应用程序的 AI 代理的技术方向。这意味着塑造我们如何与 LLM 合作解决最困难的问题：在大型代码库中保持上下文、编排感觉直观的多步骤工作流，并处理从简单的 UI 调整到复杂的架构决策等各种任务。
这不是 API 集成工作。您将定义控制 AI 如何推理和生成全栈应用程序的模式和系统，推动跨多个团队的项目，并影响我们更广泛的 AI 战略。您的工作塑造了每天使用 Bolt 构建真实产品的数百万用户的体验。
🛠️ 您将如何贡献
- 定义 AI 代理架构：确定代理如何管理上下文、编排工作流和扩展的技术方向。
- 领导多模型策略：在提供方（OpenAI、Anthropic、Google）之间建立评估和选择标准；与提供方团队合作测试新功能。
- 构建工具使用和工作流基础：设计安全、可靠的工具调用接口（搜索、查询、领域操作）；评估框架（例如 Vercel AI SDK、LangGraph）并制定组织最佳实践。
- 推动跨团队执行：协调产品/设计/工程，解决权衡问题，并指导工程师提升 AI 工程标准。
查看英文原文
🚀 About Us
We’re Bolt.new by StackBlitz!
We’re the team that brought you WebContainers, the first-of-its-kind technology that made it possible to run Node.js right inside your browser. That breakthrough kicked off our journey in 2019, and it’s what powers the blazing-fast online IDE used by over 1 million developers every month.
But we didn’t stop there.
We doubled down on everything we learned and built — the fastest way to go from idea to production without writing traditional code. It’s a next-gen, AI-powered app builder that helps you create, edit, and deploy full-stack web and mobile apps instantly, right in your browser. No installs. No setup. Just smart automation and instant dev environments that let you move at the speed of thought.
We’re a fully remote team, globally distributed, deeply collaborative, and seriously passionate about building the future of software development.
This is your chance to join a small team with a big vision. If you love shipping fast, solving real problems, and pushing the boundaries of what’s possible, we’d love to meet you.
✨ About This Opportunity
As a Staff Engineer on the AI team, you'll lead the technical direction of the AI agents that turn natural language into production-ready applications. This means shaping how we work with LLMs to solve our hardest problems: maintaining context across large codebases, orchestrating multi-step workflows that feel intuitive, and handling everything from simple UI tweaks to complex architectural decisions.
This isn't API integration work. You'll define the patterns and systems that govern how AI reasons about and generates full-stack applications, driving initiatives across multiple teams and influencing our broader AI strategy. Your work shapes the experience of millions of users building real products with Bolt every day.
🛠️ How You'll Contribute
- Define AI Agent Architecture:Set technical direction for how agents manage context, orchestrate workflows, and scale.
- Lead multi-model strategy: Build evals and selection criteria across providers (OpenAI, Anthropic, Google); partner with provider teams to test new capabilities.
- Build tool-use & workflow foundations: Design safe, reliable interfaces for tool calling (search, queries, domain actions); evaluate frameworks (e.g., Vercel AI SDK, LangGraph) and set org best practices.
- Drive cross-team execution: Align product/design/engineering, resolve tradeoffs, and mentor engineers to raise AI engineering standards.
- Establish data & evaluation standards: Own dataset methodology and the eval harness; turn failure modes and conversation insights into measurable improvements.
- Drive Research and Innovation: Experiment with prompting, context handling, and post-training; share learnings externally when appropriate.
💡 Qualifications
- Deep LLM experience: Built and scaled production LLM systems; strong grasp of capabilities, limits, and emergent behavior.
- Prompt engineering: Sets best practices and mentors across models and use cases.
- Software engineering: Strong fundamentals; designs scalable systems and makes pragmatic architectural calls.
- Strategic execution: Drives ambiguous, high-scope work end to end; influences across teams.
- Systems thinking: Spots process/communication/technical debt and improves team velocity.
- Model & agent literacy: Tracks coding-agent/LLM advances; understands model tradeoffs and the agent lifecycle.
- Data-driven leadership: Builds data collection + eval harnesses; turns insights into measurable improvements.
- Strong verbal and written English communication skills are required, as this role involves frequent collaboration with team members, stakeholders, and customers where English is the primary working language.
🎯 Bonus Points
- Fine-tuning and alignment of: LLMs (SFT, RLHF/RLAIF, DPO/ORPO)
- Machine Learning Background: Understanding of ML fundamentals and experience with model evaluation metrics.
- Open Source Contributions: Experience contributing to or maintaining open-source AI/ML projects.
- Research Background: Experience reading and implementing techniques from AI/ML research papers.
- External Presence: Experience speaking at conferences, publishing technical content, or representing an organization in industry forums.
📌 A Few Notes
- You do not need a college degree to apply
- You do not need to be located in the U.S. — we’re remote-friendly
- You do not need to meet every qualification listed above
Originally posted on Himalayas