New opportunity

Generative AI Trainer

Algomind Academy · Indore, India

About this role

Algomind Academy is hiring a Generative AI Trainer for its Indore campus. The on-campus role involves teaching Generative AI through offline classroom sessions, guided labs and mentor-reviewed projects, in collaboration with academic and operations teams. The posting lists a 1–6-year experience range and describes the role as full-time or part-time.

Responsibilities

Deliver structured classroom sessions using the approved curriculum, run daily hands-on labs and answer student questions.
Design assignments, assessments and mentor-reviewed projects; track progress and provide individual support to students who need it.
Update course content to reflect current industry practice and represent the academy professionally with students, parents and partners.

Required skills: LLMs and prompt engineering, RAG pipelines, LangChain, vector databases and AI app building.

Preferred qualifications

Prior teaching, training or mentoring experience; a relevant graduate or postgraduate qualification, such as B.Tech, MCA, BCA or MBA where applicable; strong spoken and written English and Hindi; and a portfolio, certifications or real project work in the relevant domain.

The posting mentions compensation aligned with experience, equipped classrooms and computer labs, skill-upgradation and certification support, opportunities for senior or leadership roles, and performance-based incentives. No salary amount is stated.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Large Language Models (LLMs)Prompt engineeringRAGLangChainVector databasesAI app developmentTeachingAssessment designEnglishHindi

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Deliver classroom teaching and daily labs
The role calls for structured offline sessions using the approved curriculum, daily hands-on practice and answers to student questions. Prepare a short lesson plan that moves from explanation to a guided exercise.
Teach practical Generative AI development
Required topics include LLMs, prompt engineering, RAG pipelines, LangChain, vector databases and AI app building. Prepare to explain how these components fit together in a working example.
Assess learning and support individuals
The trainer designs assignments, assessments and mentor-reviewed projects, tracks progress and supports students who need individual help. Prepare an example of a project brief and how you would assess its work.
Keep instruction current and coordinate delivery
The posting asks the trainer to update content to reflect industry practice, work with academic and operations teams, and communicate professionally with students, parents and partners. Prepare to discuss how you would propose a course update within an approved curriculum.

Likely challenges to think through

Balancing coverage with hands-on time
A likely teaching trade-off is covering the approved curriculum while leaving enough time for daily labs and questions; this is a preparation hypothesis, not a reported problem. Practice pacing a sample session with a clear lab outcome and room for troubleshooting.
Helping struggling students without stalling the group
Because the role includes both group labs and individual support, different learning speeds may be difficult to manage. Prepare a way to spot gaps through student work and provide focused follow-up while the rest of the class continues.
Updating fast-moving material responsibly
Current Generative AI practice may change faster than an approved curriculum. Prepare to explain how you would evaluate a proposed content update and coordinate it with the academic team rather than changing lessons unilaterally.

Practice your answers

Technical practice

How would you explain what an LLM does and where its answers can go wrong?

What to coverThe posting names LLMs as a required skill. Suggested preparation: explain token-based generation in accessible terms, then discuss limitations such as inaccurate outputs and ways to check answers in a classroom exercise.

How would you teach students to improve an ineffective prompt?

What to coverThe posting names prompt engineering and daily hands-on labs. Suggested preparation: walk through a before-and-after prompt, explaining how clearer context, constraints and output expectations affect the result.

How would you build and explain a basic RAG pipeline?

What to coverThe posting requires RAG pipelines. Suggested preparation: explain document preparation, retrieval, prompt construction and answer generation, including how you would check whether an answer is grounded in retrieved material.

What choices matter when using a vector database for retrieval?

What to coverVector databases are a stated required skill. Suggested preparation: discuss chunking, embeddings and similarity search, including the trade-off between retrieving enough context and retrieving irrelevant material.

Where would LangChain fit in an AI application?

What to coverThe posting explicitly lists LangChain. Suggested preparation: describe how you would use it to connect application components, while explaining when a simpler implementation might be easier for students to understand and debug.

How would you scope a student AI-app project?

What to coverAI app building and mentor-reviewed projects are part of the role. Suggested preparation: outline a small, testable application with clear inputs and outputs, and explain how students could demonstrate functionality and limitations.

How would you troubleshoot a RAG lab that returns irrelevant answers?

What to coverThe role includes daily labs and resolving student doubts. Suggested preparation: describe a stepwise check of the input, retrieved passages and generated response so students can locate the failure rather than only changing the final prompt.

How would you turn an approved curriculum topic into a classroom session and lab?

What to coverThe trainer must deliver structured offline sessions using the approved curriculum. Suggested preparation: explain how you would set a learning objective, demonstrate a concept, give students hands-on practice and check understanding.

How would you assess a mentor-reviewed Generative AI project?

What to coverThe posting calls for assignments, assessments, projects and progress tracking. Suggested preparation: propose criteria for technical correctness, explanation of design choices and evidence from testing, then describe feedback students could act on.

How would you decide whether course content needs updating?

What to coverKeeping content current with industry practice is a stated responsibility. Suggested preparation: explain how you would verify a proposed change, judge its relevance to the approved curriculum and make it teachable in a classroom or lab.

Behavioural practice

Tell me about a time you helped a learner who was falling behind.

What to coverThe role includes tracking progress and supporting slow learners individually. Describe the situation, the support you provided and the result, including how you checked whether the learner understood the material.

Tell me about a time you coordinated with another team to deliver learning activities.

What to coverThe posting describes collaboration with academic and operations teams. Give a real situation, your actions to align responsibilities or timing, and the result for the learning activity.

Tell me about a time you handled an unexpected question or obstacle during a practical session.

What to coverDaily labs and resolving student doubts are stated duties. Describe what happened, how you responded without losing the rest of the group, and what the outcome taught you.

Tell me about a time you explained a technical issue to a non-technical stakeholder.

What to coverThe role involves professional communication with students, parents and partners, and the posting prefers strong English and Hindi communication. Give the situation, how you adapted your explanation and the result; do not assume a particular language was required in that example.

Tell me about a time feedback led you to change how you taught or mentored.

What to coverThe role emphasizes an outcome-driven learning experience and student progress. Describe the feedback or evidence, the change you made and the observed result, distinguishing what you know from what you inferred.

Sharpen your knowledge

Topics to prepare

LLMs and prompt engineering
Required skills in the posting. Revise how instructions, context and output constraints affect responses; compare three prompts for the same teaching example and explain the differences to a beginner.
RAG pipeline concepts
RAG pipelines are required. Sketch the steps from document preparation and retrieval to answer generation, then identify where an irrelevant source could produce a weak answer.
Vector database fundamentals
Vector databases are required. Revise embeddings, similarity search and retrieval limits; explain how you would check whether retrieved passages answer a student’s question.
LangChain’s role in an AI application
LangChain is required. Map where it would connect prompts, retrieval and model calls in a simple application; distinguish those components before practising implementation.
Learning and assessment design
The role includes assignments, assessments, mentor-reviewed projects and individual support. As preparation, outline how one RAG lesson could progress from explanation to lab, assessed task and feedback.

Skills to revise

Build a small AI application
AI app building is required. As a practice exercise, implement a simple question-answering application and be ready to explain its inputs, outputs, limitations and design choices.
Run a guided RAG lab
Daily hands-on labs and the required RAG, LangChain and vector database skills make this directly relevant. Prepare a short lab that builds a retrieval-and-answer flow, includes a checkpoint and shows how to diagnose a poor result.
Deliver a short classroom lesson
Structured offline sessions and doubt resolution are explicit responsibilities. Rehearse a brief explanation of prompt engineering, followed by a learner exercise and answers to two likely questions.
Create and review an assessment
The posting calls for assignments, assessments, mentor-reviewed projects and progress tracking. Draft one AI-app task, a suggested scoring rubric and an example of actionable feedback for a learner needing support.
Explain technical work clearly
Strong English and Hindi communication is preferred, and the trainer interacts with students, parents and partners. Practise explaining a RAG result and its limitation in clear language; practising in both languages is a preparation suggestion, not a stated teaching-language requirement.

Your preparation checklist

Prepare a focused evidence packet
Collect examples of LLM and prompt-engineering work, RAG pipelines, LangChain, vector databases and AI app building. The posting requires these skills and prefers a portfolio, certifications or real project work.
Build a project walkthrough
Choose a real AI app or RAG project, if available, and prepare a concise explanation of its architecture, design choices, limitations and what you built yourself. Use it to support a possible portfolio review or domain task.
Rehearse a short classroom lesson
Plan a structured Generative AI lesson with a learning objective, a prompt-engineering demonstration and time for student questions. A demo lecture is listed as one possible technical assessment.
Draft a hands-on lab and assessment
Prepare a lab exercise and a follow-up assignment or project brief, including instructions, expected outputs and a simple review rubric. These reflect the role’s daily labs and mentor-reviewed projects.
Prepare a learner-support example
Outline how you would track progress, spot a learner who is struggling and provide individual help. If you have taught or mentored before, select a specific example; that experience is preferred, not required.
Practice communication and prepare questions
Rehearse clear technical explanations in English and Hindi, which the posting lists as preferred. Ask the academic team how the approved curriculum is updated, how projects are reviewed and how trainers coordinate with operations.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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