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Applications may be assessed in part using Trida's skill-based tools (verified certifications, skill tests, and FitScore), always alongside human review before any hiring decision.
Forward Deployed Engineer – Deployment Infrastructure
Company: Trida AI
Location: Austin, Texas, United States
Work Model: Remote
Employment Type: Contract
Experience: 6–11 Years
Compensation: $95–$140 per hour
About Trida AI
Trida AI is expanding its Forward Deployed Engineering bench for upcoming customer engagements. Engineers in this pool are first in line for client deployments as engagements start.
About the Role
Trida AI deploys Forward Deployed Engineers inside enterprise customer teams to design, build, and ship production AI systems — agents, retrieval, and data integrations — and to leave behind systems the customer can operate themselves. Success is production adoption and measurable workflow impact, not a demo. Travel to customer sites up to 50% may be required depending on the engagement.
What You'll Do
Lead end-to-end deployment of AI systems in private-cloud, hybrid and on-prem environments — planning, configuration, testing and rollout
Partner with customer IT on infrastructure, networking, security and data-management requirements
Troubleshoot deployment issues in constrained environments and own operational runbooks
Design for environments where public cloud is not an option
What We're Looking For
Production Kubernetes and Helm, DevOps and CI/CD depth
Deep cloud infrastructure (AWS/Azure/GCP), networking and virtualisation
Enterprise security and compliance deployment experience
Additional Information
Must be authorized to work in the US; Trida AI does not provide sponsorship. Trida AI LLC is an equal opportunity employer. We welcome applicants of all backgrounds. If you need an accommodation in the application process, contact careers@trida.ai. Location: Remote — United States (Austin, TX base).
About Trida AI
Forward-deployed AI engineers embedded in your company to build, ship, and run AI systems that actually work in production.
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