Senior AI Platform Engineer

Company:Qualcomm Incorporated
Job Area:Engineering Group, Engineering Group >
Software Engineering

General

Summary:

We are seeking a Senior AI Platforms Engineer to design, build, and operate the infrastructure that powers large-scale AI and ML workloads, with a strong focus on LLM hosting and serving at scale
. This role requires deep expertise in Kubernetes
, multi-cloud environments
, and observability systems
, as well as experience with agentic workflow orchestration (e.g., n8n) in production environments. You will collaborate with global teams to deliver secure, reliable, and cost-efficient AI platforms.

Key Responsibilities

• LLM Hosting & Serving
  • Deploy and manage large language models (LLMs) at scale using AWS Bedrock, GCP Vertex, Azure AI Foundry and Kubernetes-based solutions.
  • Optimize inference performance for throughput, latency, and cost efficiency.
• Platform Engineering
  • Build and maintain Kubernetes clusters for AI workloads with GPU scheduling, autoscaling, and high availability.
  • Model and deploy auto scaling applications and APIs to existing Kubernetes clusters
  • Implement CI/CD pipelines and Infrastructure as Code (Terraform, Helm).
• Observability & Monitoring
  • Design and implement observability stacks for large-scale systems, including metrics, logs, and traces.
• Semantic Search Systems
  • Manage large-scale search systems built on elasticsearch powering hybrid-search solutions.
• Agentic Workflow Systems
  • Deploy and scale agentic workflow orchestration systems (e.g., n8n) for AI-driven automation.
  • Ensure reliability, security, and performance of workflow execution at scale.
• Multi-Cloud Expertise
  • Operate across AWS, GCP, and Azure, leveraging managed AI services and GPU infrastructure.
• Collaboration
  • Work closely with globally distributed teams; provide documentation, mentorship, and participate in on-call rotations.

Required Qualifications

• 5–7 years of experience in platform engineering
  , MLOps
  , or SRE roles.
• Strong hands-on experience with:
  • Kubernetes (production-grade deployments, autoscaling, GPU scheduling).
  • Cloud platforms
    : AWS (Bedrock, Sage Maker), plus GCP and/or Azure.
  • Python and scripting languages (Bash, Power Shell).
  • Linux systems administration
    .
• Proven experience hosting and serving LLMs at scale in production environments.
• Expertise in observability
  :
  Elasticsearch, Prometheus, Grafana, Open Telemetry.
• Familiarity with agentic workflow systems (e.g., n8n) and scaling them for enterprise use.
• Strong understanding of networking, security, and IAM in cloud-native environments.
• Excellent communication skills and ability to work with global teams
  .

Preferred Qualifications

• Experience with model serving frameworks (vLLM, Triton, KServe, Ray Serve).
• Knowledge of vector databases (Elasticsearch vector, Milvus, Pinecone) for RAG workflows.
• Familiarity with service mesh (Istio/Linkerd),
  policy-as-code (OPA/Gatekeeper).
• GPU optimization for inference workloads.
• Certifications:
  
  AWS Solutions Architect or ML Specialty
  , CKA/CKAD
  .

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.

• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail or call Qualcomm's toll-free number found . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process.

Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications…