Senior AI Infrastructure Engineer

Staffed4U • Annapolis Junction, MD

15h • Onsite

About The Position

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.

Requirements

• 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.
• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• Medical Employer pays 100% of the monthly premium for the employee and 80% for the employee’s dependents.
• Health Savings Account (HSA) Save for all medical, dental, vision and prescription expenses by contributing pre-tax money to an HSA account. Employer contributes 50% of the annual deductible (prorated to start date).
• Dental and Vision Employer pays 100% of the monthly premium for the employee and 80% for dependents.
• Life Insurance 100% company-paid Life and Accidental Death & Dismemberment (AD&D) coverage offered to all full-time employees.
• Short-Term Disability 100% company-paid short-term disability. This benefit pays out 60% of earnings, with a $1,500 maximum for up to 12 weeks.
• Retirement Plan Automatic 6% of salary contributed to the company 401(k) plan, fully vested. Employee match encouraged but not required.
• Paid Time Off (PTO) & Holidays 5–6 weeks of PTO based on tenure with the company, in addition to 11 paid holidays.
• Tuition Reimbursement $5,000 annually for courses directly related to job role and responsibilities.
• Training Reimbursement Paid training, certification courses, and conferences to support employee career growth.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior