Clera
Founding Forward Deployed Engineer
Austin
No sponsorship$110k-$135kDetected 1 day ago
Machine LearningData EngineeringAgentic AILogisticsCustomer SuccessCommunication
About the role
- This is a high-impact, front-line role at the intersection of engineering, customer success, and product.
- You'll be the technical face of the company to US customers - embedded in their operations, solving real problems, and feeding critical insights back to the core product team.
Responsibilities
- Build repeatable deployment playbooks, integration patterns, and technical documentation to scale the US go-to-market motion
- Travel to customer sites as needed to support hands-on deployments and build strong relationships with operations and planning teams
Requirements
- 3-10+ years of experience in a forward deployed engineering, solutions engineering, technical customer success, or similar customer-facing technical role
- Experience integrating SaaS products with third-party systems (APIs, webhooks, data pipelines, etc.)
- Self-starter mentality with the ability to operate independently in an early-stage, fast-moving environment
Nice to have
- Background in logistics, fleet management, waste management, or industrial operations
- Experience at an early-stage startup or as a first/founding hire in a technical go-to-market role
- Familiarity with AI/ML-powered products or route optimization tools
- Experience working with GPS telematics or job management platforms
Compensation
- Salary: $110,000 - $135,000 USD annually
Benefits
- Founding-team equity participation
Company info
- Own end-to-end technical deployments for US customers, from onboarding through to long-term success
- Integrate the AI scheduling platform with customers' existing job management systems, GPS tools, and operational workflows
- Act as the primary technical point of contact for US customers, diagnosing and resolving issues quickly
Visa & Work Authorization
- Visa sponsorship is not available for this role.
This listing is sourced directly from Clera's careers page and normalized into a canonical job model.