Generative AI Agentic AI
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Job Location:
Monthly Salary:
Posted on:
6 hours ago
Vacancies:
1 Vacancy
Job Summary
Generative AI / Agentic AI requirement.
Final round f2f
Skill Required - Real time Gen AI RAG based Implementation project experience and not just POC experience(Gen AI RAG LLM Langchain Python or nay programming languange)
Experience - 6 to 20 years ( Senior Developer / Associate Architect / Architect/Senior Architect)
Work Mode - Permanent & Hybrid (3 days work from Office)
Work Location - Chennai / Hyderabad / Bangalore
Interview Rounds - 3 technical (one level face to face is must as per candidates convenience.)
1st level AI round - Theoritical basic Gen AI screening questions on LLM Langchain RAG etc...
2nd round - Panel - Theoritical covering all LLM RAG questions Coding
3rd round - Panel - Realtime scenario based technical questions.
Responsibilities - Ability to work across various different GenAI Models and cloud providers.
Extensive implementation experience in data analytics space or a senior developer role in one of the modern technology stack.
Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java.
Ability to build API based scalable solutions and debug & troubleshoot software or design issues.
Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java.
Ability to build API based scalable solutions and debug & troubleshoot software or design issues.
Hands on exposure to integrating atleast one of the popular LLMs(Open AI GPT PaLM 2 Dolly Claude 2 Cohere etc.) using API endpoints.
Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS
Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support
Hands on exposure to using cloud(Azure/GCP/AWS) services for storage serverless-logic search transcription and chat
Extensive experience with data engineering and should be hands on in using Agentic AI Framework RAG.
Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS
Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support
Hands on exposure to using cloud(Azure/GCP/AWS) services for storage serverless-logic search transcription and chat
Extensive experience with data engineering and should be hands on in using Agentic AI Framework RAG.
