Cognizant

Typical interview loop

How Cognizant usually runs it for applied AI and LLM engineer roles.

1. 1

   Recruiter intro call

   Focus: Background and role fit

   If your profile fits, a recruiter sets up a short call to understand your experience and how it maps to the role.

2. 2

   Online assessment

   Focus: Communication, aptitude, coding

   Depending on the role, one or more online tests covering communication, aptitude and technical skills; for freshers this includes coding and SQL.

3. 3

   Hiring-team technical interview

   Focus: Technical skills, project depth

   Interviews with the hiring team, virtual or in person, where you walk through your projects and are tested on the technical skills the role needs.

4. 4

   Client interview (some roles)

   Focus: Client fit and communication

   For client-facing project roles, a further interview with the client team who will work with you.

Topics to prepare for Cognizant

The topics its loop weighs most, each with what interviewers check and what to study.

• Retrieval for RAG: chunking, hybrid search, rerankingRAG
• Embeddings and vector searchRAG
• Behavioral interviews: STAR stories for AI engineersBehavioral
• Evaluating RAG: retrieval metrics and faithfulnessRAG
• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
• The project deep-dive roundBehavioral
• Story bankBehavioral
• Interview openers and closersBehavioral

How it weights your plan

Selecting Cognizant when you build a plan multiplies each topic’s priority score: