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Student-targeted AI intern role with popular LLM/ML skillset yields moderate applicant density.
Core CS and Python skills transfer broadly, but agentic-LLM toolset makes the role moderately specialized.
Mandatory CS fundamentals and Python plus competitive-programming preference impose moderate filtering.
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Contribute to designing and implementing multi-agent AI workflows using LangGraph and Python under senior engineer guidance.
Assist in context management engineering including context selectors, token-budgeted prompts, and typed context schemas.
Support LLM integration, retrieval systems, and quality evaluation loops to enhance production-grade AI agent systems.
Pursuing or recently completed B.Tech/B.E./M.Tech/MCA in Computer Science or related field from reputable institution.
Strong fundamentals in computer science including data structures, algorithms, and problem-solving.
Proficient in Python 3.10+ with experience in async programming and typing.
Work Experience Required: Not explicitly mentioned in the JD.
Final-year student or recent graduate with a strong competitive programming or problem-solving track record (Codeforces/LeetCode/ICPC).
Hands-on experience or strong interest in LLM integration, agentic AI components, and production-level Python coding.
Comfortable working under mentorship with focus on multi-agent orchestration, context engineering, and collaboration in a technically rigorous environment.