Senior Customer Engineer
About the role
Position Summary
We are looking for Senior Software Engineer [Customer Facing] for our customer engineering team—it is a high-impact hybrid where hardcore DevOps/SRE problem-solving meets hands-on internal tooling and direct customer consulting.
You will troubleshoot complex, often ambiguous issues for enterprise customers across cloud and container environments—tackling broken pipelines, deployment failures, connectivity problems, and misconfigured infrastructure. You will own these issues end-to-end, acting as a trusted technical advisor to customer engineering teams, and feeding crucial findings back to our core Product and Engineering orgs.
But you won't just fix problems; you will build solutions. We put a heavy emphasis on internal development to make our entire team exponentially faster. You will engineer internal tools, diagnostic utilities, and playbooks. Crucially, you will help us build the future of our operations by developing internal AI tools on top of LLMs, training models on our own proprietary data to automate diagnostics and streamline workflows.
Please note that this is a highly customer-facing role. If you have an SRE or platform background, possess the coding chops to build robust tooling, and thrive when collaborating directly with customers on complex technical challenges, this role is a perfect fit.
About the role
Customer Troubleshooting & Technical Resolution
- Be the Face of Harness: Serve as the primary technical resource for enterprise customers during complex troubleshooting, onboarding, and expansion.
- Code Fluency: Comfortable reading source code to understand how a product behaves, identify where something may be breaking, and form a hypothesis without waiting for core Engineering to explain it.
- Own complex customer issues across Kubernetes (k8s), ECS, Docker, cloud platforms (AWS, GCP, Azure), and on-premise/hybrid environments — from first contact through to resolution.
- Perform root-cause analysis on pipeline failures, deployment issues, runner/agent connectivity, secrets management errors, and service-to-service communication.
- Debug infrastructure automation, execution logs, and metrics data across CloudW