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We’re looking for an AI Solutions Architect Intern to help design and prototype AI-enabled solutions that deliver measurable value. You’ll work with business users, engineering, data science, security, and cloud/platform teams to translate business problems into scalable AI architectures. This internship is hands-on: you will contribute to reference architecture, proof-of-concepts, and implementation playbooks for real-world use cases.
Job Responsibility:
Partner with stakeholders to gather requirements and translate them into AI solution designs and technical plans
Create end-to-end architecture diagrams for AI/ML and GenAI use cases (data ingestion → model → evaluation → deployment → monitoring)
Support building proof-of-concepts using modern AI tooling (LLMs, vector databases, prompt orchestration, model serving)
Help define best practices for model lifecycle: experimentation, evaluation, responsible AI, observability, and cost controls
Assist in designing secure, compliant architectures (PII handling, access controls, audit logging, data governance)
Document solution patterns, reusable components, and developer enablement materials
Present findings and demos to technical and non-technical audiences
Requirements:
Ability to work full-time for 12 weeks during Summer 2026
program dates are May 18th – August 7th, 2026, OR June 15th – September 4th, 2026
Currently pursuing a BS/MS in Computer Science, Engineering, Data Science, or related field
Familiarity with Python and basic software engineering practices (Git, testing, APIs)
Understanding of core ML concepts (training vs inference, evaluation, overfitting, metrics)
Strong communication skills and ability to explain technical ideas clearly
Understanding of AI/ML concepts and algorithms
Strong problem-solving skills and ability to work in a fast-paced environment
Nice to have:
Exposure to GenAI/LLMs (prompting, embeddings, RAG, evaluation techniques)
Security/privacy awareness (PII/PHI concepts, least privilege, threat modeling)