AI Forward Deployed Engineer
Job ID: 112639
Location: St. Louis, Missouri [Remote]
Category: Infrastructure
Employment Type: Contract
Date Added: 05/18/2026
Role Summary
An AI Forward Deployed Engineer is responsible for bridging advanced AI solutions with production environments, ensuring seamless deployment, integration, and operation of AI inference systems. This role requires a technically proficient professional capable of handling customer-facing deployments, system troubleshooting, and performance tuning across cloud, on-premises, and hybrid infrastructures. The engineer will collaborate closely with data science, engineering, and operations teams to deliver reliable and secure AI-driven solutions in a fast-paced environment.
Responsibilities
- Lead the end-to-end deployment of AI models and inference systems into customer production environments.
- Integrate AI solutions with existing enterprise systems, APIs, and data pipelines.
- Design and implement optimized AI inference architectures focusing on latency, throughput, and cost-efficiency.
- Support and manage cloud, on-premises, and hybrid deployment models, tailoring approaches to customer needs.
- Ensure post-deployment system stability, performance, and reliability of AI solutions.
- Develop automation scripts and tools to streamline AI operations and improve efficiency.
- Implement observability frameworks, including logging, metrics, tracing, and alerting, to monitor AI workloads.
- Perform performance tuning and resource optimization for inference pipelines and supporting infrastructure.
- Act as the primary technical contact for customers during deployment, troubleshooting, and support phases.
- Collaborate across teams to translate technical requirements and feedback for continuous improvement.
Qualifications
- 4+ years of experience in deployment engineering, solutions engineering, or machine learning engineering roles.
- Proven experience deploying and maintaining AI/ML models in production environments.
- Strong proficiency in Python and shell scripting for automation and system integration.
- Hands-on experience with AI inference frameworks and model serving platforms such as TensorRT, Triton, TorchServe, or vLLM.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
- Experience deploying workloads on major cloud platforms including AWS, Azure, or GCP.
- Working knowledge of observability tools including Prometheus, Grafana, Datadog, or OpenTelemetry.
- Ability to troubleshoot complex technical issues in customer-facing settings.
- Effective communication skills for engaging technical and non-technical audiences.
- Availability to work in a fully remote environment.
Publishing Pay Range: $45.00 – $51.00 Hourly
This is a fully remote role and can be performed from an approved location.
