Forward Deployed AI Engineer

webAI•Austin, TX

22h•Hybrid

About The Position

As a Forward Deployed AI Engineer at webAI, you will be on the front lines of integrating cutting-edge AI solutions into real-world enterprise environments. You will work directly with customers to understand their needs, deploy AI systems into their infrastructure, and ensure high performance and reliability at scale. You’ll help bridge the gap between research, engineering, and operations—playing a pivotal role in building the future of edge AI. This role will require a minimum of 25% travel, including occasional on-site work at customer locations to support deployment, troubleshooting, and integration of our platform within enterprise environments.

Requirements

5+ years of combined experience in software engineering, field engineering or deployment engineering.
Proven track record of deploying and maintaining machine learning/AI systems in production.
Scripting/automation ability (Python, Bash, or similar) to turn manual deployment steps into repeatable processes.
Experience debugging complex systems involving data pipelines, model inference, and hardware interaction.
Exceptional communication skills; able to challenge vague requirements and turn them into actionable plans.
Comfortable working in dynamic environments with high customer exposure.

Nice To Haves

Experience deploying models on edge devices or consumer hardware.
Familiarity with distributed systems, DevOps tooling, and performance tuning.
Prior experience in a customer-facing engineering role.
Knowledge of privacy-preserving AI and secure compute environments.
Master’s degree in a relevant technical discipline.

Responsibilities

Own the deployment runbook and continuously improve it based on what breaks in the field
Serve as the technical point of contact for customers during deployment and early production phases
Build and maintain internal tooling to make deployments faster, more repeatable, and less dependent on tribal knowledge
Collaborate closely with customers to scope, deploy, and maintain AI solutions in production environments.
Debug and optimize data pipelines and AI systems running on customer networks.
Translate complex, often ambiguous customer requirements into well-scoped technical solutions.
Serve as a trusted technical advisor to enterprise clients, representing the engineering team externally.
Contribute feedback and insight to internal teams to continuously improve product robustness and usability.