Senior Software Engineer II - Agentic Intelligence

Honeycomb is a developer-tools company focused on observability. The Senior Software Engineer II will design, build, and maintain production-grade AI agents that investigate, reason over, and act on live observability data in Canvas, while extending related agent surfaces and evaluation capabilities.

Tags

Big Data

Enterprise Software

Cloud Computing

Software

Information Technology

Analytics

Application Performance Management

Cloud Data Services

Data Visualization

Developer Tools

DevOps

Software Engineering

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

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

Preferred

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

Benefits

A stake in our success - generous equity with employee-friendly stock program

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

AI-ready observability platform for production systems.

San Francisco, California, USA

https://www.honeycomb.io

Late Stage

Total Funding

$146.9M

Key Investors

Headline

Insight Partners

Scale Venture Partners

2023-04-06

Series D· $50M

2021-10-20

Series C· $50M

2021-02-02

Series B· $20M

Leadership Team

Christine Yen

Co-founder/CEO

Charity Majors

Co-Founder/CTO

Recent News

Qualifications

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

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

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

You understand how a fast, high-cardinality data store changes what an agent can reason about, and how to design for that

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

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

Required skills

AI and Agent Engineering, Agent Architecture, LLM Evaluation Frameworks, LLM-Based Systems, Product Judgment, Prompt Engineering, Retrieval-Augmented Generation (RAG)