AI Platforms Leader, Enterprise AI Platforms

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$202,900–$304,300 / yr
Posted
50 days ago
Freshness
Confirmed live today
Closes
Mar 16, 2027
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k
This role $254k
$146k $321k
below market most similar roles pay here above market

This role pays more than 82% of similar roles. Most pay $167,650–$246,150 — the blue band above. At the midpoint, this role pays about $254k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$218,400 across 551 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · AI Platforms Leader, Enterprise AI Platforms

Role Posting Log in to save

The AI Platforms Leader oversees the strategy, architecture, and operations of the end-to-end AI Platform, managing a global team of engineers. This role involves owning the multi-year vision for a multi-tenant, hybrid infrastructure spanning on-prem GPU clusters and cloud services like AWS, GCP, and Azure. Key responsibilities include operating GPU clusters using Kubernetes and Slurm, delivering MLOps and LLMOps products, and designing agentic orchestration systems including A2A patterns and MCP servers. The position requires expertise in high-throughput storage, vector databases, and model gateways like Triton or vLLM. You will implement CI/CD pipelines using Terraform, Bicep, and Helm while ensuring security through RBAC and secrets management. The work focuses on providing reliable, cost-efficient, and secure self-service platform capabilities for training, fine-tuning, and inference.

Skills

MLOps LLMOps Kubernetes AWS Azure GCP Terraform Python PyTorch CUDA Triton Inference Server vLLM KServe Slurm Docker CI/CD GitOps Bicep Helm Ray MLflow Airflow Argo LangChain CrewAI AutoGen Vector Databases FAISS Milvus Pinecone Lustre BeeGFS Ceph NCCL

What you'll do

  • Define the multi-year strategy and roadmap for a multi-tenant, hybrid AI platform.
  • Operate and optimize on-prem GPU clusters using Kubernetes, Slurm, and high-throughput networking.
  • Deliver MLOps and LLMOps products including data prep, model registries, and automated CI/CD pipelines.
  • Design and operate agentic orchestration systems, tool integrations, and MCP servers.
  • Manage multi-cloud AI services on AWS, Azure, and GCP with robust cost and security controls.
  • Own core platform services including identity, service meshes, vector stores, and model gateways.
  • Lead a global engineering team of 10 engineers with 24/7 readiness and incident response.
  • Manage strategic vendors and negotiate licenses to align with the platform roadmap and budget.

What we're looking for

  • Must have a Bachelor's degree in Engineering, Computer Science, or a related field.
  • Must have 15+ years of overall engineering experience, including 10+ years building and operating large-scale platforms.
  • Must have 5+ years of experience leading a team of approximately 10 engineers.
  • Must have hands-on experience operating on-prem GPU clusters using Kubernetes and/or Slurm.
  • Must have deep experience with AWS, GCP, or Azure AI/ML services and managed Kubernetes.
  • Must have experience with MLOps/LLMOps, including model lifecycle management, evaluation, and observability.
  • Must have experience with CI/CD, GitOps, and Infrastructure as Code tools like Terraform, Bicep, or Helm.
  • Must have a solid understanding of agentic AI, A2A patterns, and operating MCP servers in production.

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