AI-Driven Cloud Customer Experience Engineer

Jobicy; United States; Remote; USD 100,000 - 135,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive healthcare benefits

FSA

Flexible work schedule

Employee Assistance Program

Flexible Time Off & Parental Leave

Team events

Internet reimbursement

Job summary

Harness is the AI Software Delivery Platform company led by Jyoti Bansal. We are seeking a Customer Engineer to own complex enterprise issues in collaboration with Product and Engineering.

You'll resolve deployment failures, broken pipelines, and misconfigurations across Kubernetes, Docker, and cloud environments, while building reusable diagnostics and tooling and mentoring junior engineers. This role offers hands-on coding and opportunities to influence internal AI tooling.

Qualifications

• 2+ years in a customer-facing engineering, DevOps, SRE, or platform role.
• Hands-on with Kubernetes, ECS, and Docker, plus at least one cloud platform (AWS, GCP, or Azure).
• Solid grasp of CI/CD concepts and Linux networking.
• Scripting ability (Python, Node.js, Bash) and coding exposure to read/modify source.
• Clear written and verbal communication for customer calls and findings.
• Fast learner, comfortable working in unfamiliar systems.

Responsibilities

• Own customer cases end-to-end on your team, triage and resolve across Kubernetes, ECS, Docker and cloud environments.
• Contribute to customer-facing tooling and small product fixes with Product and Engineering.
• Lead or participate in customer calls and screen shares, communicating findings clearly.
• Build internal scripts and diagnostics to speed up casework and expand AI tooling exposure.
• Turn recurring patterns into run books, playbooks, and reusable templates.

Skills

Kubernetes

ECS

Docker

Cloud platforms

CI/CD

Scripting

Communication

Job description

Harness is the AI Software Delivery Platform company led by Jyoti Bansal. We are seeking a Customer Engineer to own complex enterprise issues in collaboration with Product and Engineering.

You'll resolve deployment failures, broken pipelines, and misconfigurations across Kubernetes, Docker, and cloud environments, while building reusable diagnostics and tooling and mentoring junior engineers. This role offers hands-on coding and opportunities to influence internal AI tooling.