Senior Forward Deployed AI Engineer

Special Notice: This position is not contingent upon awarding of a project or needing a funding source. This is direct, full-time employment with webAI. About the Role: We are seeking a Senior Forward Deployed AI Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments. This role sits at the intersection of machine learning, systems engineering, and deployment optimization, bridging research and real world implementation. You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments. The ideal candidate will be based in Austin, Texas or in the Washington, D.C./Northern Virginia area. On a case-by-case basis, we will consider fully remote candidates. Qualified candidates who are not based in Austin, Texas may be asked to travel to our Austin, Texas headquarters. This role will require up to 25% travel, including occasional on-site work at customer locations to support deployment, troubleshooting, and integration of our platform within enterprise environments. Key Responsibilities: Collaborate closely with customers to scope, deploy, and maintain AI solutions in production envir [... source excerpt omitted ...] deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems. Debug and optimize data pipelines and AI systems running on customer networks. Translate complex, often ambiguous customer requirements into well-scoped technical solutions. Work across the stack—from model inference on consumer hardware to infrastructure automation. Read hardware schematics/logs to identify performance bottlenecks and suggest improvements. 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 [... source excerpt omitted ...] of combined experience in software engineering and machine learning. Active US Security clearance Proven track record of deploying and maintaining machine learning/AI systems in production. Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc. 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. Preferred Qualifications: Experience deploying models on edge devices or consumer hardware. Familiarity with distributed syst