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Generative AI Developer - 27th Feb (Friday)- Virtual Interview

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Onsite

Generative AI Developer - 27th Feb (Friday)- Virtual Interview

Tata Consultancy Services

Generative AI Developer - 27th Feb (Friday)- Virtual Interview

Skills

SQL QueriesDeep LearningDjangoFlaskPythonNumPypandasPyTorchTensorFlowPostgreSQLNeo4jMachine LearningAIAWSTalent AcquisitionNLP / Natural Language ProcessingFastAPIFullstack DevelopmentAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Kochi, Kerala, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


Job title: Gen AI & Agentic AI Developer

Experience Range: 3 -12 Years

Location: Kochi

Virtual Interview : 27th Feb - Friday

Timing : 10 am - 4pm

Job Description:

Must Have Technical/Functional Skills

  • GenAI & LLM Frameworks
  • Vector Databases (e.g., AWS OpenSearch & Kendra, FAISS, Pinecone)
  • Word and Vector Embeddings (e.g., Word2Vec, BERT, Sentence Transformers)
  • Frameworks & Toolkits (AWS Bedrock, LangChain, LangGraph, LlamaIndex)
  • Cloud - AWS (preferably), Azure
  • Agentic AI & Automation - AWS Bedrock Agents, LangGraph, AutoGen, CrewAI
  • Programming & ML Skills
  • Python (mandatory), SQL (Postgres), NoSQL (Dynamo DB, Mongo DB), Graph DB (Neo4j,

Neptune)

  • Libraries numpy, pandas, boto3, plotly, matplotlib, seaborn, ggplot, Scikit-learn,

Requests, Beautiful Soup, NLTK)

  • ML algorithms (Supervised, Unsupervised and Ensemble) & Deep Learning (using

frameworks like TensorFlow, PyTorch, etc.)

  • Web Development frameworks – (Django, Flask, FastAPI)
  • Conversational AI
  • Chatbot development using LLMs or traditional NLP pipelines
  • UI development using Python Streamlit or Gradio libraries

Roles & Responsibilities

  1. Design, develop, and fine-tune AI models using prompt engineering, fine-tuning, and retrieval-

augmented generation (RAG).

  1. Implement and optimize large language model (LLM) workflows using LangChain, LangGraph, and

LlamaIndex.

  1. Develop and orchestrate intelligent agents and agentic workflows for task automation.

  2. Integrate vector databases and embedding techniques (word/vector embeddings) for semantic

search and knowledge retrieval.

  1. Build, test, and deploy chatbots and AI systems tailored to business requirements.

  2. Apply machine learning & Deep Learning models for classification, segmentation, and regression

problems. 7. Integration with platforms and APIs 8. Collaborate with cross-functional teams to deliver production-grade AI applications.

Human Resources - TCS

Talent Acquisition Group

Tata Consultancy Services

Let's connect on Linkedln: linkedin.com/in/mahalaxmi-g-46a391245

For Opportunities visit: https://ibegin.tcs.com/iBegin

Website: www.tcs.com

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