Principal Engineer – Distributed AI Systems Architecture, Heterogeneous Compute

Intel Corporation

. Define a runtime model for executing AI workloads as distributed computation graphs across heterogeneous resources .

Posted 4/22/2026full-timeSanta Clara • California, Oregon, Texas • 🇺🇸 United StatesLead💰 $255,850 - $361,200 per yearWebsite

Tech Stack

Tools & technologies

Distributed Systems

About the role

Key responsibilities & impact

Define a runtime model for executing AI workloads as distributed computation graphs across heterogeneous resources
Design abstractions for graph representation, dependencies, and execution semantics
Enable dynamic scheduling and execution across CPUs, GPUs/specialized accelerators, and IPUs/FNICs.
Architect systems where state (e.g., KV cache) is a first-class concern in scheduling and execution
Develop mechanisms to analyze AI computation graphs and classify stages by: compute intensity, memory bandwidth requirements, communication cost, latency sensitivity
Architect frameworks that treat specialized accelerators (e.g., dataflow engines) as first-class execution targets
Design runtime strategies for Mixture-of-Experts (MoE) models, including: expert placement, routing locality, load balancing vs data movement trade-offs
Define observability and telemetry models for distributed AI execution
Build feedback loops that continuously optimize placement, scheduling, and resource utilization

Requirements

What you’ll need

Bachelor's or BS degree in Computer Science, Software Engineering, or a related specialized field, or equivalent experience per business needs.
12-plus years of experience with a Bachelor's degree
Proven expertise in defining and implementing software architectures for AI frameworks, protocols, and algorithms.
Deep experience in systems architecture, high-performance computing, or distributed systems
Strong background in parallel or data-parallel computation models
Experience with heterogeneous compute environments (CPU, GPU, DSP, or accelerators)
Proven ability to design end-to-end systems from abstraction through implementation
Strong understanding of performance trade-offs across compute, memory, and interconnect.

Benefits

Comp & perks

competitive pay
stock bonuses
benefit programs which include health
retirement
vacation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI workloadsdistributed computation graphsdynamic schedulingexecution semanticscompute intensity analysismemory bandwidth requirementsMixture-of-Experts (MoE) modelsparallel computation modelshigh-performance computingsystems architecture

Soft Skills

problem-solvinganalytical thinkingcommunicationcollaborationleadership