Honeycomb.io - Senior Software Engineer II - Agentic Intelligence
Requirements
• 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. • End-to-end ownership. • 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. • Current judgment, not just past experience. • 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. • Agent architecture depth. • 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. • Product judgment. • 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. • Observability or developer-tools background. • 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!) • 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. • Please note we cannot currently sponsor or support visa transfers at this time. • 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: • @honeycomb.io • We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—never personal accounts like Gmail or Yahoo. • never personal accounts like Gmail or Yahoo • never • 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.
Responsibilities
• 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. • Design and deliver production-grade agents. • 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. • Own the agent work; support the whole product. • 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. • Build agents only Honeycomb can build. • 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. • Extend the surface, and decide what's next. • Define what "good" means for agents here. Set the bar: measurable against real evals, maintainable, and honest about their limits. • Define what "good" means for agents here. • 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). • Multiple agents collaborating on one shared Canvas investigation • 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). • Auto-investigation the moment an SLO burn alert fires • Skills that encode a team's domain expertise e.g. Kubernetes thresholds so agents and human colleagues can lean on them (o11ycon 2026). • Skills that encode a team's domain expertise
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