We are looking for enthusiastic and curious engineering students to join us as AI Agent Interns. In this role, you will help design, prototype, and validate enterprise use cases for AI agents and automated workflows that demonstrate tangible AI leverage across business functions.
This is a hands-on opportunity to work at the intersection of Generative AI, automation, and real-world business problem solving, turning emerging AI capabilities into practical solutions that create measurable value for the organization.
AI is reshaping how enterprises operate, but the real advantage comes from applying it to the right problems. As an intern on this team, you will help identify high-impact use cases, build working prototypes of AI agents and workflows, and contribute to a portfolio of AI-powered solutions that the organization can showcase and scale.
You will get exposure to: Enterprise AI strategy in action; Agent design patterns (tool use, retrieval, multi-step reasoning); Workflow automation across departments (HR, Finance, Operations, Customer Support, etc.); and Prompt engineering, LLM integration, and evaluation.
This is an equal-opportunity internship. We welcome applicants from all backgrounds and institutions.
Key Responsibilities
Use Case Discovery & Research
- Collaborate with internal teams to understand business processes and pain points.
- Research and benchmark existing AI agent and workflow solutions in the market.
- Document potential use cases with feasibility, impact, and effort estimates.
- Prioritize use cases based on business value and technical viability.
Prototyping & Development
- Build functional prototypes of AI agents for targeted enterprise tasks (e.g., document Q&A, data extraction, internal knowledge assistant, support triage).
- Design and implement automated workflows using LLMs, APIs, and orchestration tools.
- Integrate AI agents with internal systems, databases, or knowledge bases where applicable.
- Apply prompt engineering best practices to optimize agent performance.
Testing & Evaluation
- Define evaluation metrics (accuracy, latency, cost, user experience).
- Test agents against real or simulated enterprise data.
- Identify failure modes, edge cases, and improvement opportunities.
- Document findings and iterate on designs.
Documentation & Showcasing
- Create clear documentation for each use case: problem statement, solution architecture, demo flow, and results.
- Prepare demo-ready presentations and walkthroughs for stakeholders.
- Contribute to an internal AI Use Case Library that the organization can leverage and present externally.
Collaboration & Learning
- Work closely with mentors, engineers, and business stakeholders.
- Participate in design reviews, brainstorming sessions, and knowledge-sharing forums.
- Stay current on AI agent frameworks, tools, and industry trends.
Qualifications & Experience
| Education | Currently pursuing B.Tech / B.E. / M.Tech in Computer Science, IT, Electronics, AI/ML, Blockchain, or a related field |
|---|---|
| Year of Study | In their 2nd, 3rd, or 4th year of study (preferred) |
Requirements
- Strong problem-solving and analytical thinking.
- Excellent communication, ability to explain technical concepts to non-technical stakeholders.
- Self-driven and curious, willingness to explore new tools and learn independently.
- Ability to work in a team and take ownership of assigned use cases.
What We Offer
- Real-world experience building AI agents for enterprise scenarios.
- A portfolio of working prototypes you can showcase.
- Mentorship from experienced AI and engineering professionals.
- Understanding of how AI drives value in a business context.
- Certificate of completion / letter of recommendation based on performance.