DevOps Engineer IV - US
About The Position
Rackspace Technology is the trusted operator of the full enterprise AI stack, from governed private cloud to AI inference and agents in production. From edge to core to cloud, we operate the infrastructure, data layer, and software integration to deliver business outcomes with the predictable cost, reliability, security, and compliance that regulated and mission-critical environments demand. We support customers in more than 120 countries with AI capabilities spanning private cloud, public cloud, applications, data and cyber resilience. Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience.
- 6–9 years of experience in technology, with significant infrastructure ownership.
- 4–6 years hands-on architecting/optimizing cloud infrastructure and CI/CD systems.
- 1+ year informally mentoring engineers or leading design reviews.
- Advanced expertise in cloud infrastructure, containerization/orchestration, and IaC; independently designs highly available, cost-optimized architectures.
- Independently designs CI/CD systems and deployment pipelines, including LLMOps pipelines for AI/ML models.
- Deep understanding of AI infrastructure operational signals (latency, token cost, drift) and designs monitoring/alerting for them.
- Mentors mid-level and junior engineers on infrastructure design and secure AI-endpoint practices.
- Occasionally presents technical work to cross-functional groups of 5–10 people.
Nice To Haves
- Cloud Professional-level certification.
- Deep experience with LLMOps at scale (GPU provisioning, vector DB hosting)
Responsibilities
- Architect and own end-to-end delivery of complex infrastructure and CI/CD systems, including LLMOps pipelines, spanning multiple services.
- Lead design reviews and set technical direction for own area; mentor junior/mid engineers.
- Lead incident response and root-cause analysis for high-impact infrastructure issues within own domain.
- Help secure AI endpoints and agentic tools against prompt-injection and data-leakage risks for owned systems.
- Contribute to and help enforce security/compliance controls across infrastructure.
- Serve as a primary technical liaison to stakeholders, translating needs into the team's infrastructure/AI-ops roadmap.
- Participate in the on-call rotation for after-hours and weekend support.
Benefits
- annual bonus or incentives
- equity awards
- Employee Stock Purchase Plan (ESPP)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
