обновлено 5 дней назад
AI Automation Engineer (AIOps)
124 397 - 138 003$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Automation Engineer (AIOps): Modernizing critical enterprise systems through AI-powered infrastructure, agentic AI workflows, MCP servers, and secure deployment pipelines with an accent on end-to-end automation, Kubernetes, Terraform, Ansible, and CI/CD. Focus on designing secure MCP server ecosystems, building autonomous agent skills, and deploying reliable AI-augmented operations in mission-critical environments.
Location: Fully remote/telework or hybrid/flex within the United States; U.S. citizenship required
Salary: USD $124,397–$138,003 per year
Company
develops high-technology solutions, products, and services for defense, scientific, and mission-critical applications.
What you will do
- Modernize critical enterprise systems through intelligent automation, AI-powered infrastructure, and agentic AI workflows.
- Design and implement end-to-end automation solutions using GitLab CI, Kubernetes, Terraform, and Ansible.
- Build and manage secure, scalable CI/CD pipelines for testing, deployment, and operational workflows.
- Design, deploy, and manage MCP servers that expose tools, data sources, and APIs to AI agents and LLM-powered workflows.
- Build agent skills and multi-step workflows that interact autonomously with infrastructure, pipelines, operational systems, databases, and third-party APIs.
- Apply AIOps principles, automated compliance, self-healing infrastructure, and proactive reliability engineering in regulated and mission-critical environments.
Requirements
- Bachelor’s degree in Software Engineering or a related science, engineering, technology, or mathematics field, plus 5+ years of job-related experience; alternatively, a master’s degree plus 3 years of experience.
- U.S. citizenship is required.
- Experience with Kubernetes, Terraform, Ansible, and GitLab CI for infrastructure automation, container orchestration, and CI/CD.
- Experience deploying AI/ML models, LLM-based assistants, or agentic frameworks in production or operational environments.
- Understanding of prompt engineering, retrieval-augmented generation, MCP, OAuth 2.0/OpenID Connect, token management, scoped permissions, and least-privilege access.
- Ability to design secure AI integrations and reliable automation for complex, regulated, or mission-critical environments.
Culture & Benefits
- Research-oriented work focused on practical solutions for national security.
- Flexible schedules, including an optional every-other-Friday-off 9/80 schedule.
- 401(k) matching, flexible time off, paid parental leave, and healthcare benefits.
- Health and wellness programs, employee resource groups, and social groups.
- Opportunities for continuous learning and career development.
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