As a Support Enablement Engineer Intern, you will play a critical role in executing and implementing AI-driven enablement initiatives that transform how Dropbox delivers customer support at scale. Embedded within the Customer Experience (CX) organization, you will help operationalize AI capabilities, automate support workflows, and strengthen the systems that empower our global support teams.

This is a highly hands-on, execution-focused role where you will contribute directly to real-world AI enablement projects. Your work will streamline support operations, improve agent efficiency, and elevate customer outcomes. By collaborating closely with cross-functional technology partners across Dropbox, you will help translate emerging AI capabilities into practical, scalable solutions that meaningfully enhance the customer support experience.

In our Virtual First work culture, you’ll connect with with Dropboxers virtually and in-person to build the foundation of a strong professional network. As a Summer intern, you will also have the opportunity to attend our Emerging Talent Summit, where participants from our intern and early-career programs come together in person to build lasting relationships, explore learning and development opportunities, and prepare for their career journey ahead.

For Summer 2026, we offer two start dates culminating in a 12-week internship:

• May 26 - August 14, 2026
• June 30 - Sep 18, 2026

• Support the execution and rollout of AI-driven enablement initiatives across Customer Experience (CX) support workflows, working under the guidance of enablement engineers and AI Program Manager.
• Assist in designing, testing, and deploying AI-powered workflows, such as:
• Monitor and troubleshoot issues related to CX tools and AI integrations, helping ensure system reliability, performance, and scalability.
• Analyze support and operational data to identify opportunities for AI-driven automation and workflow improvements.
• Collaborate with cross-functional partners across CX, Customer Experience & Success (CXS) Tech, and Go-to-Market (GTM) Platforms teams to ensure AI solutions align with real customer support needs and operational constraints.
• Develop and deploy automation scripts, configurations, or integrations to support AI enablement efforts.

• Currently pursuing an undergraduate degree in Computer Science, Information Technology, Information Systems, Systems Engineering, or a related technical field, with an expected graduation date in 2027.
• Demonstrated interest in solutions engineering, technology enablement, workflow automation, and applying AI-driven solutions to operational problems.
• Hands-on experience through coursework, projects, internships, or labs with AI, APIs, system integrations, or workflow automation concepts.
• Foundational familiarity with AI-enabled systems or tools used to support operational workflows (e.g., agent assist, knowledge retrieval, intelligent routing, or similar applications), either through academic projects, tooling exposure, or self-directed learning.
• Experience with at least one programming or scripting language (e.g., Python, JavaScript) and comfort working in a development or configuration-based environment.
• Analytical mindset with the ability to interpret data, identify patterns, and translate insights into practical process or tooling improvements.
• Ability to work independently on well-scoped tasks while collaborating effectively with cross-functional partners in a virtual team environment.
• Ability to clearly explain technical concepts to both technical and non-technical audiences.
• Curious, adaptable, and motivated to learn, iterate, and apply new technologies, particularly AI to real-world customer support and operational challenges.
• Exposure to CX tools (e.g., ticketing systems, knowledge bases, internal tooling) is a plus but not required

• Exposure to Customer Experience (CX) or support operations: Including hands-on experience with support tooling, case workflows, or service operations environments through internships, part-time roles, or academic projects.
• Experience building or configuring automation: Including scripts, integrations, or low-code/no-code workflows that reduced manual effort or improved operational efficiency.
• Familiarity with data analysis or visualization: To measure adoption, performance, or outcomes, using tools such as dashboards, spreadsheets, SQL, or similar analytics platforms.
• Experience collaborating cross-functionally with technical and non-technical partners to translate requirements into practical solutions.
• Demonstrated interest in applied AI enablement: Including experimentation with AI tools, prompt iteration, model outputs, or human-in-the-loop workflows in operational contexts.
• Hands-on experience with modern AI technologies and workflows, such as LLMs (ChatGPT, Claude, Gemini), automation platforms (n8n, Make, Gumloop), building AI agents, API integrations, MCP, AI coding assistants (Cursor, Claude Code), and no/low-code AI platforms (Lovable, Replit, Bolt).

US Pay Range

$5,000—$6,000 USD