AI Solution Architect - Graduate Intern

AI in this role

Support AI accelerator platforms, cluster deployments, system validation, and AI workload benchmarking as an AI Solution Architect Intern.

vllmpytorchtensorflowpythonlinux

ragai-automationcomputer-visionai-infrastructurecluster-operationssystem-validationmachine-learning

Job Details:

Job Description:

Intel is seeking an AI Infrastructure Solution Architect Intern to join our AI Platforms team. As an intern, you will work alongside experienced engineers to support AI accelerator platforms, cluster deployments, system validation, and AI workload benchmarking. This role provides hands-on experience across AI infrastructure, system software, cluster operations, firmware debugging, and end-to-end AI solution development.

The ideal candidate is passionate about AI systems, computer architecture, Linux, and large-scale computing environments, and enjoys solving complex technical problems.

Responsibilities

AI Infrastructure and Cluster Operations:

Assist in deploying and validating AI accelerator systems and multi-node AI clusters.
Support cluster bring-up activities, including system provisioning, software installation, and health verification.
Execute performance benchmarks and collect system telemetry.
Help troubleshoot system, networking, and software issues in AI environments.

System Debugging and Validation:

Analyze hardware, firmware, driver, and software logs to identify failures.
Assist with validation of BIOS, firmware, and system software configurations.
Support development of test plans and automated validation workflows.
Participate in root-cause investigations of system performance and stability issues.
AI/ML Workloads
Deploy and evaluate AI models using frameworks such as PyTorch and vLLM.
Benchmark AI workloads and identify performance bottlenecks.
Assist in reproducing customer-reported issues in lab environments.
Contribute to optimization studies for AI inference and training workloads.

Automation and Tool Development:

Develop Python-based tools to automate testing, monitoring, and data collection.
Create dashboards, scripts, and utilities for cluster management and diagnostics.
Contribute to documentation, runbooks, and technical knowledge bases.
End-to-End AI Solutions
Participate in building end-to-end AI solutions, such as generative AI, agentic AI, computer vision, robotics, or intelligent automation projects.
Work with cross-functional teams to integrate hardware, software, AI models, and applications into complete solutions.

Qualifications:

Minimum Qualifications

Currently pursuing Master's in: Computer Science, Computer Engineering, Electrical Engineering, Data Science, or AI/ML or related fields
Experience with Python programming.
Familiarity with Linux command line and system administration concepts.
Understanding of computer architecture, operating systems, networking, or distributed systems.
Demonstrated ability to solve complex engineering or technical problems through coursework, research, personal projects, robotics competitions, hackathons, open-source contributions, or previous internships.
Strong analytical and problem-solving skills.
Ability to work independently and collaborate in a team environment.

Preferred Qualifications

Technical Skills - Experience with:

Python, C/C++, or Bash scripting
Linux/Unix environments
Git and software development workflows
Docker or containerized applications

Familiarity with:

PyTorch, TensorFlow, or other AI frameworks
LLMs, RAG, agentic AI, or generative AI applications
Cloud or cluster computing environments
GPU or AI accelerator technologies

Project Experience - Coursework, research, personal projects, or internships involving:

AI/ML applications
Robotics systems
Autonomous systems
Computer vision
Distributed computing
High-performance computing (HPC)
End-to-end AI solution development

Soft Skills:

Strong communication and presentation skills.
Curiosity and willingness to learn new technologies.
Ability to diagnose problems systematically and communicate findings clearly.

What You Will Learn:

• AI accelerator and cluster architecture
• AI infrastructure deployment and operations
• System-level debugging and performance optimization
• AI model deployment and benchmarking
• Automation, monitoring, and validation frameworks
• Customer-facing AI solution development and deployment best practices

Job Type:

Student / Intern

Shift:

Shift 1 (United States of America)

Primary Location:

US, California, Santa Clara

Additional Locations:

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $133,498.00-133,502.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Our standard internship rates are based on your degree, location, and the job role. Your recruiter can share more about the specific compensation range for your preferred location and job role during the hiring process.

Work Model for this Role

This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

How we rate this

AI Solution Architect - Graduate Intern at Intel rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

AI Solution Architect - Graduate Intern is an open job at Intel.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $133k-$134k a year.
The role is based in US, California, Santa Clara.
The job was posted on October 5, 2026.
Seniority: intern.
Applications are handled by Intel. Apply on Intel

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI AutomationComputer VisionAI InfrastructureCluster OperationsSystem ValidationMachine LearningvLLM

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Tell me about a workflow you automated with AI tools, end to end.
Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a project where ai infrastructure was part of your work. What did you do?
Tell me about a project where cluster operations was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, AI Automation, Computer Vision, AI Infrastructure, and Cluster Operations. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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