AI Platforms Leader (Enterprise AI Platforms)

Stack

Responsibilities

• ▹Define the multi-year strategy and roadmap for a multi-tenant, hybrid (on-prem + cloud) AI platform
• ▹Establish platform SLAs/SLOs, reliability goals, and security/compliance guardrails
• ▹Operate and optimize on-prem GPU clusters (Kubernetes + GPU operator and/or Slurm), capacity planning and scheduling
• ▹Deliver MLOps/LLMOps as a product: data prep, training/fine-tuning, model registry, governance, evaluation, safe deployment
• ▹Implement CI/CD for models, prompts, and agents with automated evaluation and canary/A-B rollouts
• ▹Lead agentic AI orchestration (A2A patterns) and MCP server integration
• ▹Leverage cloud AI/ML platforms (AWS/Azure/GCP) for training and inference
• ▹Own core platform services: identity/RBAC, secrets, observability, vector stores, model gateways
• ▹Lead a ~10-engineer global platform/SRE/MLOps team with 24x7 on-call readiness and incident response
• ▹Manage strategic vendor relationships and licensing

Requirements

• ▹15+ years overall engineering/technology experience, including ~10 years building and operating large-scale platforms (AI/ML, data, or HPC)
• ▹5+ years leading a ~10-engineer team across platform/SRE/MLOps/LLMOps
• ▹Hands-on experience operating on-prem GPU clusters (Kubernetes + GPU operator and/or Slurm)
• ▹Strong MLOps/LLMOps experience across the full model lifecycle (data → training → registry → deployment)
• ▹Deep AWS/GCP/Azure experience with managed Kubernetes (EKS/AKS/GKE)
• ▹DevOps/platform engineering: CI/CD, GitOps, IaC (Terraform/Bicep/Helm), Docker, Kubernetes
• ▹Understanding of agent orchestration, A2A patterns, and operating MCP servers in production
• ▹Bachelor's degree in Engineering, Computer Science, or related field

Nice to have

• ▹Master's or PhD in CS/EE/Math or related field
• ▹Experience with PyTorch, CUDA/cuDNN, Triton Inference Server, vLLM, KServe, Ray, Slurm
• ▹High-throughput storage (Lustre, BeeGFS, Ceph) and vector databases (FAISS, Milvus, Pinecone)
• ▹MLOps toolchain: MLflow, Airflow/Argo, Weights & Biases, LangSmith
• ▹Security/governance: OIDC/RBAC, OPA policy as code, AWS Secrets Manager/Azure Key Vault
• ▹Agentic frameworks: Semantic Kernel, LangChain, CrewAI, AutoGen

Soft skills

What we offer

• ▹Competitive annual discretionary bonus program
• ▹Opportunity for annual RSU grants
• ▹Highly competitive benefits package

About the company

Qualcomm Incorporated is a global technology company. This role sits within the Engineering Group's Software Engineering organization, building and operating the company's enterprise-wide AI platform infrastructure.