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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Infrastructure Engineer - **Company:** Staffed4U LLC - **Location:** Annapolis Junction, MD, United States - **Experience:** Expert - **Salary:** $293,000.0 - $306,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Application Performance Management, Computing Platforms, Cloud Computing, Cloud Engineering, Encodings, Information Systems, Computer Engineering, Data Infrastructure, DevOps, Distributed Systems, Python (Programming Language), Prometheus, Search Technologies, Service-Oriented Architecture, Software Deployment, Software Engineering, Systems Architecture, Systems Integration, Web Applications, Workflow Management Systems, AI Infrastructure, Data Logging, Enterprise Software Applications, Cloud Platform System, High Performance Computing, System Availability, Large Language Models, Grafana, Multi-Agent Systems, Software Security, Generative AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations - **Published:** June 18, 2026 - **Apply:** https://www.clearancejobs.com/jobs/8983721/senior-ai-infrastructure-engineer ## About the Role * Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related technical discipline and eight (8) years of relevant experience; OR * Four (4) additional years of directly related experience may be substituted for the degree requirement. Technical Qualifications * Demonstrated experience building, deploying, and maintaining enterprise-scale production systems. * Experience designing and supporting high-volume web applications and distributed service architectures. * Strong background in systems integration across diverse technologies, platforms, and cloud environments. * Hands-on experience designing, deploying, and operating cloud infrastructure in Amazon Web Services (AWS). * Experience administering and deploying applications using Kubernetes. * Strong software development skills using Python. * Experience implementing observability and monitoring solutions using technologies such as: + Application Performance Monitoring (APM) tools + OpenTelemetry + Grafana + Prometheus * Experience developing and maintaining Continuous Integration and Continuous Deployment (CI/CD) pipelines. * Knowledge of DevOps principles, automation practices, and modern software delivery methodologies. * Demonstrated ability to lead technical initiatives and influence engineering practices across teams. * Ability to operate effectively in dynamic environments with evolving requirements. * Excellent written and verbal communication skills., * Experience supporting AI model deployment, serving, and inference platforms. * Experience integrating generative AI and large language model (LLM) technologies into enterprise applications. * Experience with AI workflow orchestration frameworks, including LangChain or similar technologies. * Knowledge of vector databases, embedding technologies, and semantic search solutions. * Experience implementing Retrieval-Augmented Generation (RAG) architectures. * Experience with distributed computing, high-performance computing, or large-scale processing environments. * Familiarity with autonomous agent frameworks and emerging AI technologies. Knowledge, Skills, and Abilities * Strong cloud engineering and platform architecture expertise. * Deep understanding of distributed systems and cloud-native application design. * Ability to balance reliability, security, scalability, and performance requirements. * Strong analytical and problem-solving skills. * Ability to lead technical initiatives and influence organizational technology adoption. * Strong collaboration and stakeholder engagement skills. * Excellent organizational skills and attention to detail. * Ability to mentor engineers and contribute to a culture of technical excellence. ## Description We are seeking an experienced Senior AI Infrastructure Engineer to support the design, deployment, and operation of enterprise artificial intelligence and machine learning platforms. This role will be responsible for developing and maintaining scalable infrastructure that enables the delivery of AI-powered applications and services across the organization. The successful candidate will independently design, implement, and operate cloud-native infrastructure components while supporting modern AI technologies, distributed systems, and production service environments. This position requires strong expertise in platform engineering, cloud technologies, automation, observability, and software development., * Design, implement, and optimize infrastructure supporting AI model deployment and inference at scale. * Develop, maintain, and support production AI services and applications. * Collaborate with stakeholders and engineering teams to define technical solutions for evolving business and operational requirements. * Design and implement scalable, reliable, and maintainable platform architectures. * Drive adoption of emerging technologies, engineering best practices, and automation solutions. * Implement monitoring, logging, alerting, and observability capabilities for platform services. * Automate infrastructure provisioning, configuration, and lifecycle management using Infrastructure-as-Code (IaC) methodologies. * Ensure high availability, reliability, performance, and scalability of platform services. * Support the secure deployment and operation of AI systems and associated data environments. * Contribute to system architecture reviews, platform modernization efforts, and operational support activities. * Provide technical guidance, knowledge sharing, and mentorship to engineering team members. * Participate in troubleshooting, root cause analysis, and continuous improvement initiatives. ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)