AI Model Serving Specialist

Rackspace

54d • $82,300 - $140,580

About The Position

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.

Requirements

• 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.

Nice To Haves

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

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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees