远程工作雷达

高级软件工程师 II - 自主智能

Senior Software Engineer II - Agentic Intelligence

AI开发工程限定地区(需当地身份)
公司honeycomb
薪资未公开
工作地点Remote - United States
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-07-30
数据来源Greenhouse
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注意地域限制:该职位明确限定在 Remote - United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

我们正在构建什么

Honeycomb 是一项面向现在和未来的服务,重新定义了可观测性,并提升了开发者工具所能实现的期望!我们与 HelloFresh、Slack、LaunchDarkly 和 Vanguard 等知名公司合作,覆盖多个行业。这是我们发展过程中的一个激动人心的时刻,我们完成了 D 轮融资,员工人数超过 200 人,并被列为 Forbes 2022 年和 2023 年美国最佳初创公司!

如果你想知道我们最近在做什么,请查看这些博客文章和 Honeycomb.io 的新闻稿。

我们是谁

我们因影响力而来,因文化而留下!我们是一群才华横溢、有主见、充满热情、极度包容且负责任的团队成员。我们有坚定的信念,并努力每天践行我们的价值观。我们希望我们的员工能在一支才华横溢(但谦逊)的团队中做他们真正热爱的事情。

我们如何工作

我们是一家完全分布式公司,这意味着我们认为最重要的是你如何交付成果,而不是你坐在哪里。我们投资于我们的员工,关心你如何适应我们的文化和流程。同时,我们从第一天起就赋予大量的信任、自主权和责任感。#LI-Remote

关于这个职位

Honeycomb 的 AI 代理可以调查、推理并基于真实的可观测性数据采取行动。它们存在于 Canvas:一个代理式的工作空间,工程师在这里了解他们的系统。

代理智能团队已经推出了 Canvas、Honeycomb MCP 服务器以及 Canvas 代理和 Canvas 技能界面。我们现在寻找的人具备深厚的代理专业知识,并能利用它来扩展团队能够构建的内容:新的代理、Canvas 中的新界面区域、记忆功能、空间感知能力,以及在我们的 Bedrock 循环上的性能提升。

Honeycomb 的数据存储速度快,可接受高基数数据;这使得建立在其之上的代理与其他基于传统可观测性后端的代理不同。这个职位是利用这一特性来构建其他可观测性产品无法做到的事情的代理。

一些工作将从原型开始。预期是代码能够完整地经历整个开发周期,从最初的粗糙版本到可以在生产环境中运行的版本。

你会做什么

  • 设计并交付生产级代理。构建能够在 Canvas 内部对实时可观测性数据进行调查、推理并采取行动的代理。这些代理必须让工程师在高压环境下也能信赖。
查看英文原文

What We’re Building

Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!

If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases.

Who We Are

We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers.

How We Work

We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote

About the role

AI agents at Honeycomb investigate, reason, and act on real observability data. They live in Canvas: the agentic workspace where engineers go to understand their systems.

The Agentic Intelligence team has shipped Canvas, the Honeycomb MCP server, and the Canvas Agent and Canvas Skills surfaces. What we're looking for today is someone who brings deep agent expertise and uses it to expand what the team can build: new agents, new surface area in Canvas, memory, spatial awareness, improved performance on our Bedrock loop.

Honeycomb's data store is fast and accepts high cardinality data; that's what makes agents built on top of it different from anything built on a conventional observability backend. This role is about taking advantage of that building agents that can do things no other observability product can do because the underlying data makes it possible.

Some of this work will start as a prototype. The expectation is that the code makes it through the full arc, from the rough first version through to something that holds up in production.

What you'll do

  • Design and deliver production-grade agents. Build agents that investigate, reason, and act on live observability data inside Canvas. These agents must be trustworthy to engineers in high pressure situations, including mid-incident. Take one from rough first version to something that holds up under production traffic.
  • Own the agent work; support the whole product. Scope, build, ship, and maintain the agents including the evals that tell you whether they got better or are just different. This role is agent-focused and also includes some fullstack development.
  • Build agents only Honeycomb can build. Use a data store that returns high-cardinality queries in seconds to reason over signal a conventional backend can't serve at this fidelity correlating across services, drilling into a single trace, comparing before and after a deploy.
  • Extend the surface, and decide what's next. Ship new capability into Canvas, the MCP server, and Canvas Skills memory, spatial awareness, a faster Bedrock loop and make the case for what comes after with working code. Distinguish hype from signal in a field with plenty of both.
  • Define what "good" means for agents here. Set the bar: measurable against real evals, maintainable, and honest about their limits.

Example projects

  • Multiple agents collaborating on one shared Canvas investigation each claiming a hypothesis, publishing findings, and narrowing the search space for the others so it resolves faster (blog).
  • Auto-investigation the moment an SLO burn alert fires the agent forms hypotheses and prepares visualizations before a human looks, cutting mean-time-to-insight for on-call (o11ycon 2026).
  • Skills that encode a team's domain expertise e.g. Kubernetes thresholds so agents and human colleagues can lean on them (o11ycon 2026).

What you'll bring:

  • AI and agent engineering experience. You've shipped LLM-based systems people relied on in production not demos, not fine-tuned models in a research context. You know where agent systems break and how to design around it.
  • End-to-end ownership. On a small team there's no handoff queue. You can take something from rough prototype to production-grade without needing someone behind you to do the durable engineering.
  • Current judgment, not just past experience. You have informed opinions about what's shifted in agent design in the last six to twelve months that would change how you'd build today.
  • Agent architecture depth. You understand how a fast, high-cardinality data store changes what an agent can reason about, and how to design for that.
  • Product judgment. You can look at what the agent layer does today and see what it should do next and make that case with a prototype, not a deck.

Even better

  • Observability or developer-tools background. Engineers are your users; you'll ramp faster with fluency in that world, and the work is better.
  • Familiarity with eval frameworks, agent tooling, RAG, and prompt engineering.

Base Salary based on level of experience
$183,340—$206,000 USD

What you'll get when you join the Hive:

  • A stake in our success - generous equity with employee-friendly stock program
  • It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
  • Time to recharge with unlimited PTO
  • A distributed-first mindset and culture (really!)
  • Home office, co-working, and internet stipend
  • Full benefits coverage for employees, with additional coverage available for dependents
  • Up to 16 weeks of paid parental leave, regardless of path to parenthood
  • Annual development allowance
  • And much more...

Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.

Phishing and Recruitment Scam Warning:

We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you:

  • All communications will come from an @honeycomb.io email address
  • We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—never personal accounts like Gmail or Yahoo.
  • Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to:
  • Social security or tax identification numbers
  • Credit card numbers
  • Bank account information

Diversity & Accommodations:

We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams.

We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know.

As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback.

Privacy Notice:

If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes.

For more information regarding our privacy practices please see the Honeycomb Privacy Notice.

If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

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薪酬经理

honeycombRemote - United States22 天前
职能支持限定地区(需当地身份)

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