Senior Forward-Deployed AI Engineer (Public Sector)

webAI

United States

On-site

USD 140,000 - 230,000

Full time

6 days ago
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Benefits offered by this job

Equity options
Parental leave
401(k)
Health coverage
Learning stipend
Remote-first

Job summary

webAI is seeking a Senior Forward Deployed AI Engineer to drive production AI solutions for public sector initiatives in the United States. You will transform prototypes into scalable systems, deploy across government cloud and edge devices, and work with customers to scope and maintain deployments.

The role blends ML, systems engineering, and deployment optimization. Ideal candidates bring 5+ years in software and ML, strong communication, and proven success in production ML deployments on

Qualifications

  • 5+ years of combined experience in software engineering and machine learning.
  • Proven ability to transform prototypes into production systems.
  • Experience deploying ML/AI in secure, distributed environments.
  • Strong communication and customer-facing collaboration.

Responsibilities

  • Transform prototypes into scalable, production AI systems.
  • Deploy AI solutions across government cloud and edge devices.
  • Collaborate with customers to scope, deploy, and maintain systems.
  • Design workflows for multi-step reasoning and tool use.
  • Debug data pipelines and optimize performance on customer networks.
  • Read hardware logs to identify bottlenecks and propose fixes.
  • Represent the team as a technical advisor to enterprise clients.

Skills

Software engineering
Machine learning
Distributed systems
Edge computing
DevOps practices
Communication

Education

Master's degree in a technical field

Tools

PyTorch
TensorFlow
ONNX
JAX

Job description

webAI is seeking a Senior Forward Deployed AI Engineer to drive production AI solutions for public sector initiatives in the United States. You will transform prototypes into scalable systems, deploy across government cloud and edge devices, and work with customers to scope and maintain deployments.

The role blends ML, systems engineering, and deployment optimization. Ideal candidates bring 5+ years in software and ML, strong communication, and proven success in production ML deployments on

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