Builds AI and LLM observability capabilities across data ingestion, infrastructure, analysis, and product visualizations. The role develops systems surfacing cost, token usage, errors, and anomalies; contributes to data models; collaborates with product and design; and ships customer-facing SaaS features. Engineers participate in on-call rotation, experimentation, and fast feedback cycles, with opportunities to work on production LLM and agent-powered features.
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
The team builds observability for AI in Honeycomb. We help customers see what their agents are doing, what those agents cost, and where errors happen. We also give them insight into individual conversations so they can debug them. We're bringing LLM and agent observability together, and we own both the data foundation and the product experiences built on top of it. You'll work in a small, cross-functional group of engineers with a dedicated product manager and designer, shipping features customers use in production. If you want to define how people understand and debug AI systems, this is the team for you.
What you’ll do in the role:- Deliver AI observability capabilities end to end, from ingestion to in-product visualizations.
- Contribute to the data model and infrastructure that let us observe agents and their ecosystems across the Honeycomb product.
- Build systems that analyze and surface AI-specific signals, such as cost, token usage, errors, and anomalies.
- Collaborate with product and design partners to make sure what we build is usable, intuitive, and unlocks meaningful user workflows.
- Share what you learn about exploring and understanding AI system behavior across conversations and workloads.
- Iterate through fast feedback loops and experimentation, and share both wins and failures.
- 3+ years of software engineering experience.
- Experience shipping customer-facing features at a SaaS company, beyond internal tooling.
- Full-stack range, with proficiency in backend development (Go and/or Python) and frontend development (TypeScript and React).
- A track record of working with product managers and designers.
- Regular, hands-on use of AI tools in your day-to-day engineering work.
- Experience being on call. You'd join our rotation after about 90 days.
- A track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job.
- Bonus: Experience building LLM or agent-powered features in production.
- Bonus: Hands-on experience with observability tooling, such as OpenTelemetry.
Base Salary based on level of experience
$160,000—$180,000 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 [email protected]. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.
Similar Jobs
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Provides field-based automotive diagnostic, repair, and technical support to GM dealerships. Resolves escalated vehicle issues, supports potential repurchase cases, evaluates dealership service readiness, trains dealer personnel, manages dispatch cases, and communicates product-quality findings to GM engineering and service teams. The role also supports warranty-cost reduction, dealer comeback processes, customer relationships, arbitration matters, and technician recruitment while traveling frequently throughout the assigned territory.
Top Skills:
Automotive Diagnostic EquipmentLan/WanMS OfficePicoscopeTechline Diagnostic Tools
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead end-to-end ML projects for automotive manufacturing: design, train, validate, deploy, and monitor models; implement MLOps/CI-CD; perform data engineering, EDA, and model evaluation; ensure data security and regulatory compliance; document and communicate results to stakeholders.
Top Skills:
Azure MlKubeflowMlflowNoSQLPythonPyTorchScikit-LearnSQLTensorFlowVertex AiXgboost
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads the strategy and execution of AI model performance and on-vehicle inference for autonomous driving. Responsibilities include managing engineering leaders, setting performance budgets, optimizing models and GPU systems, establishing benchmarking and profiling practices, detecting regressions, building performance dashboards, and guiding cross-functional architecture and production decisions. The role also oversees hiring, coaching, staffing, KPIs, technical leadership development, and trade-offs across latency, memory, throughput, accuracy, power, and numerical parity.
Top Skills:
Autonomous DrivingBenchmarkingC++Computer VisionCudaEdge HardwareGpu ProfilingGpu SystemsInference RuntimesKernel OptimizationKnowledge DistillationMachine LearningMemory OptimizationModel OptimizationNvidia Nsight ComputeNvidia Nsight SystemsPerformance DashboardsPruningPythonPyTorchPytorch ProfilerQuantizationReduced PrecisionRoboticsTelemetryTensorrt
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

