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AI Model Serving Specialist

Role Purpose


Enable enterprise customers to operationalize AI workloads by deploying and optimizing model-serving platforms (e.g., NVIDIA Triton, vLLM, KServe) within Rackspace’s Private Cloud and Hybrid environments. This role bridges AI engineering and platform operations, ensuring secure, scalable, and cost-efficient inference services.


Key Responsibilities : -

Model Deployment & Optimization 

Package and deploy ML/LLM models on Triton, vLLM, or KServe within Kubernetes clusters.

Tune performance (batching, KV-cache, TensorRT optimizations) for latency and throughput SLAs.


Platform Integration 

Work with VMware VCF9, NSX-T, and vSAN ESA to ensure GPU resource allocation and multi-tenancy.

Implement RBAC, encryption, and compliance controls for sovereign/private cloud customers.


API & Service Enablement 

Integrate models with Rackspace’s Unified Inference API and API Gateway for multi-tenant routing.

Support RAG and agentic workflows by connecting to vector databases and context stores.


Observability & FinOps 

Configure telemetry for GPU utilization, request tracing, and error monitoring.

Collaborate with FinOps to enable usage metering and chargeback reporting.


Customer Engineering Support 

Assist solution architects in onboarding customers, creating reference patterns for BFSI, Healthcare, and other verticals.

Provide troubleshooting and performance benchmarking guidance.


Continuous Improvement 

Stay current with emerging model-serving frameworks and GPU acceleration techniques.

Contribute to reusable Helm charts, operators, and automation scripts.



Required Skills & Experience
  • Hands-on experience with NVIDIA Triton, vLLM, or similar serving stacks.
  • Strong knowledge of Kubernetes, GPU scheduling, and CUDA/MIG.
  • Familiarity with VMware VCF9, NSX-T networking, and vSAN storage classes.
  • Proficiency in Python and containerization (Docker).
  • Understanding of observability stacks (Prometheus, Grafana) and FinOps principles.
  • Exposure to RAG architectures, vector DBs, and secure multi-tenant environments.
  • Excellent problem-solving and customer-facing communication skills.


Preferred Certifications
  • NVIDIA Certified Professional (AI/ML)
  • Kubernetes Administrator (CKA)
  • VMware VCF Specialist
  • Rackspace AI Foundations (internal)


KPI's
  • Model deployment success rate and SLA compliance.
  • Latency/throughput benchmarks per SKU.
  • Customer satisfaction (NPS) for AI services.
  • Efficiency in GPU utilization and cost optimization.


Physical Demands
  • General office environment: no special physical demands required.
  • May require long periods of sitting and viewing a computer monitor.
  • Schedule flexibility to include working weekends and/or evenings and holidays as required by the business for 24/7 operations.


Travel
  • As per business needs


Sponsorship
  • This role is not sponsorship eligible
  • Candidates need to be legally allowed to work in the US for any employer


$82,300 - $140,580 a year
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $82,300/year in our lowest geographic market up to 140,580/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives, equity awards and an Employee Stock Purchase Plan (ESPP). Learn more about benefits at Rackspace.

#LI-VM1

#LI-US




"Remote postings are limited to candidates residing within the country specified in the posting location"


About Rackspace Technology

We are the multicloud solutions experts. We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.

 

 

More on Rackspace Technology

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.

Average salary estimate

$111440 / YEARLY (est.)
min
max
$82300K
$140580K

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Founded in 1998, Rackspace provides multi-cloud computing solutions and services. Offering advising to customers based on business challenges, designing solutions, building, and managing solutions. The company is headquartered in San Antonio, Texa...

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Full-time, remote
DATE POSTED
December 17, 2025
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