Location
Greater Noida, Uttar Pradesh
Work Mode
Hybrid
Duration
2 months
Stipend
₹20,000/mo
Start Date
Immediate / Rolling
Openings
2 positions
Type
Full-time
Category
Artificial Intelligence
About the Internship
CrowdStrike is hiring a RAG & LLM Engineer Intern in Greater Noida — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to retrieval-augmented generation rather than a certificate-only programme.
About the role
As a RAG & LLM Engineer Intern at…
About CrowdStrike
CrowdStrike offers a mentor-led RAG & LLM Engineer Intern in Greater Noida with live project work in artificial intelligence, a stipend of ₹20,000/month and a Pre-Placement Offer opportunity for strong performers.
See all CrowdStrikeinternships →Greater Noida, Uttar PradeshVerified employer2 openings
Apply to CrowdStrike →Skills Required
Retrieval-Augmented Generation (RAG)Vector Databases (Pinecone / Chroma)EmbeddingsPythonLangChain / LlamaIndexChunking StrategiesLLM EvaluationDocument ParsingREST APIsLatency & Cost Tuning
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (CSE/IT/AI-ML), MCA or M.Sc (CS / Data Science) who are based in or willing to work from Greater Noida. You should be keen to learn Retrieval-Augmented Generation (RAG), Vector Databases (Pinecone / Chroma), Embeddings on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.
Perks
Exposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship Certificate
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Team-fit / behavioural interview with the team
- 3Online aptitude / domain assessment
- 4HR discussion — stipend, start date, expectations and offer
₹20,000/month
Stipend · 2 months
Openings2 positions
Applicants0 applied
ModeHybrid
CategoryArtificial Intelligence
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