Resident Architect- Latam

Honeycomb Honeycomb · Enterprise · Brazil · Remote · Customer Success

This role is for a Resident Architect at Honeycomb, a company focused on observability and developer tools. The role involves leading customers in the strategic application of Honeycomb and Observability practices, acting as a trusted advisor on telemetry schema design and data modeling, and becoming a subject-matter expert in sampling strategies. The architect will also mentor engineering teams, advise on telemetry ownership and standards, troubleshoot customer issues, create content, and represent the voice of the customer internally. The role requires deep understanding of OpenTelemetry, strong intuition for telemetry data modeling, ability to understand application architecture for instrumentation, and working knowledge of cloud platforms and IaC tools. Experience in Software Development or System Operations, particularly with distributed systems, is preferred, along with fluency in programming languages like Ruby, Python, Go, JavaScript, Java, or .NET. Bonus points for experience in Customer Success, TAM, Sales Engineering, Consulting, Distributed Tracing concepts, and public speaking.

What you'd actually do

  1. Lead customers in the strategic application of Honeycomb and Observability practices to meet their stated technical and business goals, including shaping how their telemetry data is structured, governed, and used across their organization
  2. Partner with Customer Success Managers and Account Executives to articulate the Honeycomb value proposition, vision, and strategy at the executive and technical levels
  3. Act as a trusted advisor on telemetry schema design and data modeling, helping customers think through how to structure events, attributes, and relationships so their data is queryable, meaningful, and durable over time
  4. Become a subject-matter expert in the practice of Sampling and the operations of our Refinery sampling, advising customers on sampling strategies that balance cost, fidelity, and operational insight
  5. Work hands-on with, teach, coach, and mentor engineering teams and leaders in Observability, SRE concepts, and instrumentation best practices

Skills

Required

  • Deep understanding of OpenTelemetry, its projects, components, SDKs, and ecosystem
  • Ability to guide customers through complex instrumentation decisions
  • Strong intuition for how telemetry data should be modeled and organized
  • Ability to understand application's architecture and flow well enough to instrument it effectively and advise others doing the same
  • Working knowledge of popular cloud platforms (AWS, GCP, or Azure)
  • Working knowledge of Infrastructure-as-Code tooling (Terraform, Kubernetes, Helm)
  • Working knowledge of CI/CD platforms and practices (CircleCI, GitHub Actions, etc.)
  • Previous experience in Software Development or System Operations
  • Experience with distributed systems at scale
  • Fluency in at least one of: Ruby, Python, Go, JavaScript, Java, or .NET
  • Excellent written and verbal technical communication skills
  • Ability to tailor depth and framing for both engineering teams and technical leadership

Nice to have

  • Previous experience in Customer Success, Technical Account Management, Sales Engineering, or Consulting
  • Deep understanding of Distributed Tracing concepts (Context Propagation, Sampling, Visualization, etc.)
  • Experience helping engineering organizations define internal observability standards, tagging taxonomies, or telemetry governance practices
  • Public speaking experience, conference talks, internal tech talks, webinars, etc.
  • Familiarity with multiple languages and/or frameworks

What the JD emphasized

  • Deep understanding of OpenTelemetry, its projects, components, SDKs, and ecosystem, along with the ability to guide customers through complex instrumentation decisions
  • Strong intuition for how telemetry data should be modeled and organized: what makes an event schema useful vs. noisy, how to think about cardinality, and how to design for long-term queryability