As a motivated PhD student with strong backend fundamentals who is excited about building production AI systems. This role is a great fit for an aspiring software engineer who works comfortably in AI-driven problem spaces and wants to apply software engineering rigor to create LLM-backed products and platforms.

This is not a research-only role. While we work closely with research and science teams, this position sits squarely in a product engineering organization. The focus is on designing and building reliable systems that ship real value to customers and internal users. We value curiosity, experimentation, and a commitment to continuous learning.

What will you do?

As an AI Software Engineering Intern, you will own an end-to-end project from idea to functioning prototype, with a clear path to production. You will:

• Develop Backend Services: Design and build services in Python that power AI-driven products and shared capabilities.
• Integrate Systems: Build resilient service integrations across internal systems, handling failure modes and rate limits.
• Build AI Features: Develop and evolve LLM-backed features and agentic workflows, focusing on reliability and real-world behavior.
• Collaborate Cross-Functionally: Work with product managers, researchers, and senior engineers to turn loosely defined AI use cases into concrete, production-ready systems.
• Shape AI Quality: Help build or extend evaluation harnesses, benchmarks, or feedback loops for AI-powered features.
• Engage in Sprints: Work at a fast pace in two-week sprints and participate in weekly meetups to share progress and technical challenges.

What skills and knowledge should you bring?

• Academic Background: Currently enrolled in a PhD program in Computer Science, Software Engineering, or a related quantitative field, graduating in 2027
• Python Proficiency: Excellent modern Python engineering skills, with the ability to write readable, performant, and testable code.
• AI Fundamentals: A strong background in AI/ML and experience with independent projects using LLMs, foundation models, or retrieval-augmented generation (RAG).
• System Design: Solid understanding of software engineering principles, including APIs, version control, and system architecture.
• Communication: Excellent communication skills and a collaborative approach to solving complex problems.
• Cybersecurity Interest: Curiosity about applying AI to cybersecurity or hands-on experience in the domain.

Why us? 

Our global internship program trains the next-generation of cybersecurity talent across a range of specializations, from threat intelligence to information security, engineering and marketing. Interns can learn about the network security industry from leading thinkers, grow their professional networks, and be part of a career-defining experience including: 

• 1:1 mentorship
• The opportunity to expand your knowledge and work on challenging projects
• Training and Development opportunities 
• Connections to other recent grads, and employees across the company
• Leadership speaker series where you can learn about other areas of the business and ask questions to the senior leadership team and industry experts
• Fun events!

As an AI/Machine Learning Engineer Intern, you will be tasked with applying software engineering skills to create reliable, AI-powered products within a fast-paced product engineering environment. You will own an end-to-end project from initial idea to a functioning prototype with a clear path to production. Throughout the internship, you will collaborate with research teams and senior engineers to transform loosely defined AI use cases into concrete, production-ready systems.

What Will You Do?

Primary responsibilities include:

• Develop Backend Services: Design and build services in Python that power AI-driven products and shared capabilities.
• Integrate Systems: Build resilient service integrations across internal systems, specifically handling complex failure modes and rate limits.
• Build AI Features: Develop and evolve LLM-backed features and agentic workflows, focusing on reliability and real-world behavior.
• Shape AI Quality: Help build or extend evaluation harnesses, benchmarks, and feedback loops to ensure the high performance of AI-powered features.
• Engage in Sprints: Work at a high velocity in two-week sprints and participate in weekly meetups to share technical progress and solve challenges.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• Advanced Academic Background: Currently enrolled in a program in Computer Science, Software Engineering, or a related quantitative field (graduating in 2027).
• Python Proficiency: Excellent modern Python engineering skills with the ability to write readable, performant, and testable code.
• AI Fundamentals: A strong background in AI/ML and experience with independent projects using LLMs, foundation models, or RAG.
• System Design: A solid understanding of software engineering principles, including APIs, version control, and system architecture.
• Cybersecurity Interest: A genuine curiosity about applying AI to cybersecurity or hands-on experience in the domain.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.