Harness
Customer Engineer
U.S · Exec
Sponsorship not specified$121k-$148kDetected 34 days ago
AWSGCPAzureCloud PlatformsDockerKubernetesTerraformPrometheusDatadogA/B Testing
About the role
- Technical Troubleshooting & Issue Resolution
- Debug failures across integrations, APIs, agents, scanners, pipeline configurations, and runtime environments.
- Use observability tooling (Datadog, Splunk, Prometheus, CloudWatch, or similar) to trace failures and identify root causes.
Responsibilities
- Own customer issues end-to-end - from first contact through root cause and resolution - across the product areas above.
- Reproduce bugs with clean, minimal reproduction steps and drive resolution in partnership with Engineering.
- Participate in incident triage during escalations - help coordinate, communicate clearly, and deliver precise technical findings. Ownership of escalations grows as you build experience in the role.
- Escalate issues to Engineering and Product with enough context to act immediately - reproduction steps, environment details, logs, and your own read on likely root cause.
- Maintain runbooks, troubleshooting guides, and playbooks so hard-won knowledge stays in the team.
- You will trace failures through logs and APIs, write scripts when needed, and design solutions when the problem calls for it.
- You will develop expertise in the following Harness modules over time.
Requirements
- What matters is the ability to pick up a new technical product quickly and work in depth.
Nice to have
- Experience with application security tooling - SAST, SCA, DAST, API security scanning, or similar.
- Familiarity with feature flag systems, A/B testing, or experimentation platforms.
- Hands-on experience with cloud platforms (AWS, GCP, Azure) - debugging IAM, networking, or environment-specific behaviour.
- Hands-on experience with Kubernetes (k8s), ECS, or Docker in a troubleshooting context.
- Comfortable reading source code to understand how a product works and form a hypothesis about what might be breaking.
- Infrastructure-as-Code experience - Terraform, Pulumi, CloudFormation, or similar.
- Experience with secrets management tools (HashiCorp Vault, AWS Secrets Manager, etc.).
- You Might Be a Great Fit If You Are...
Compensation
- $121,000 - $148,000 USD
- Harness in the news:
- Accelerating Our Mission to Bring AI to Everything After Code
- Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation
- How Harness runs 16 "startups within a startup" at scale | Jyoti Bansal
- Harness Research Shows AI Visibility Crisis Fueling Security Nightmare
Company info
- Accelerating Our Mission to Bring AI to Everything After Code
- Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation
- How Harness runs 16 "startups within a startup" at scale | Jyoti Bansal
- Harness Research Shows AI Visibility Crisis Fueling Security Nightmare
- Harness has been named to the Inc. Power Partner list for software delivery success
- Get on calls with customers to troubleshoot live - running screenshares, walking through logs, and driving toward resolution rather than deferring to async back-and-forth.
- Set honest expectations when issues are complex or slow-moving - customers should never be left wondering what is happening or who owns it.
- Enterprise customers using Harness security, feature management, and code coverage products will come to you with complex, often ambiguous issues - and your job is to dig in, find the root cause, and see it through to resolution.
- We are not looking for someone who routes tickets - we are looking for someone who digs in and solves problems.
- Support customers through onboarding and implementation, sharing best practices and helping them reach a stable, working configuration.
- You will own issues end-to-end, get on calls with customers, work closely with Engineering and Product to escalate and close problems quickly, and document what you learn so the whole team gets faster.
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This listing is sourced directly from Harness's careers page and normalized into a canonical job model.