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Engineering Intern – Gen AI

Drivetrain
Location
remote
Employment
Internship
Experience
0-2 years
Salary
₹Not Available

About the role

Focus on topics such as Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, Large Language Models (LLMs), and their application in Financial Planning & Analysis (FP&A) platforms.

Responsibilities

  • Develop & Experiment: Build and prototype Gen AI solutions using RAG, agentic workflows, and LLMs for FP&A use cases.
  • Collaborate: Work closely with product and engineering teams to integrate AI-driven features into the platform.
  • Optimize: Apply strong computer science fundamentals to design efficient algorithms, data structures, and scalable systems.
  • Document & Present: Clearly document your work, build workflow diagrams, and present results to the team.
  • Showcase: Complete and demonstrate end-to-end projects that highlight your technical and problem-solving skills.

Full description

We are seeking highly motivated Computer Science engineering interns passionate about Generative AI to join our team. You will work on real-world projects involving Retrieval-Augmented Generation (RAG), Agentic AI, and Large Language Models (LLMs) to enhance our FP&A (Financial Planning & Analysis) platform. This is a unique opportunity to gain hands-on experience at the intersection of AI and enterprise automation. Key Responsibilities Develop & Experiment: Build and prototype Gen AI solutions using RAG, agentic workflows, and LLMs for FP&A use cases. Collaborate: Work closely with product and engineering teams to integrate AI-driven features into the platform. Optimize: Apply strong computer science fundamentals to design efficient algorithms, data structures, and scalable systems. Document & Present: Clearly document your work, build workflow diagrams, and present results to the team. Showcase: Complete and demonstrate end-to-end projects that highlight your technical and problem-solving skills. Qualifications Academic Background: Currently pursuing or recently completed a degree in Computer Science or a related field. Technical Skills: Strong understanding of DSA (Data Structures & Algorithms), system design, and problem-solving. AI/ML Exposure: Familiarity with concepts such as RAG, Agentic AI, and LLMs. Completion of relevant projects is preferred. Practical Experience: Demonstrated ability to build and showcase end-to-end projects in AI/ML or related fields. Communication: Excellent verbal and written communication skills. Preferred Project Portfolio: Evidence of completed projects involving Gen AI, RAG, or agentic workflows. Hands-on Skills: Experience with modern AI frameworks, cloud platforms, and API integration.
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