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# Software Engineer (AI Infrastructure)

- **Company:** Visionist, Inc
- **Location:** Laurel, MD, United States
- **Experience:** Expert
- **Salary:** $115,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Engineering, DevOps, Python (Programming Language), Performance Tuning, Prometheus, Software Engineering, Systems Integration, Web Applications, AI Infrastructure, Data Logging, Grafana, Infrastructure as Code (IaC), AI Platforms, Kubernetes, Infrastructure Automation Frameworks, BIG-IP Access Policy Manager (APM)
- **Published:** July 16, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9034941/software-engineer-ai-infrastructure

## About the Role

Bachelor's degree in a technical discipline. (Additional 4 years of experience may substitute degree)

 - 8 years of experience in software development
 - Experience building and maintaining production systems at scale
 - Experience with high-volume web application architectures and performance optimization
 - Strong background in systems integration across diverse technologies and platforms
 - Hands-on experience with cloud engineering in AWS
 - Proficiency with Kubernetes administration and deployment patterns
 - Strong Python programming skills
 - Experience implementing observability solutions (APM, OpenTelemetry, Grafana, Prometheus)
 - Familiarity with CI/CD pipelines and DevOps practices
 - Strong organizational influence and change management skills
 - Ability to thrive in ambiguous environments and create structure where needed
 - Excellent communication and collaboration skills

## Description

Design, implement, and optimize infrastructure for AI model inference at scale

 - Support the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies
 - Define and implement solutions for ambiguous or underspecified systems and requirements
 - Drive adoption of new technologies and practices across engineering teams
 - Implement monitoring, logging, and observability solutions for AI services
 - Automate infrastructure provisioning and configuration using Infrastructure as Code (IaC) principles
 - Ensure the availability, reliability, scalability, and performance of AI platform components
 - Contribute to security best practices for AI systems and data
 - Provide technical guidance and mentorship to junior engineers


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