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Python Gen AI_Bangalore

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Onsite

Python Gen AI_Bangalore

Infosys

Python Gen AI_Bangalore

Skills

Google Cloud PlatformSQL QueriesBig DataDockerPythonMicroservicesPyTorchTensorFlowMachine LearningAIAWSKubernetesApache AirflowAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

9 September 2026

What they need


Job Title: Generative AI Engineer / AI Engineer

Experience: 6-10 Years
Employment Type: Full-Time

Job Summary

We are seeking a passionate Generative AI Engineer to design, develop, and deploy AI-powered solutions using state-of-the-art large language models (LLMs), multimodal models, and machine learning frameworks. The ideal candidate will have hands-on experience in building GenAI applications, prompt engineering, fine-tuning models, and integrating AI solutions into production systems.

Key Responsibilities

  • Design and develop Generative AI applications using LLMs (GPT, Llama, Claude, etc.)
  • Build end-to-end AI pipelines including data ingestion, preprocessing, model training, and deployment
  • Implement prompt engineering and prompt optimization techniques
  • Develop and maintain RAG (Retrieval-Augmented Generation) systems
  • Fine-tune and customize open-source and proprietary large language models
  • Integrate AI services via APIs and SDKs into enterprise applications
  • Work with vector databases (FAISS, Pinecone, Weaviate, ChromaDB)
  • Ensure model performance, scalability, and reliability in production
  • Collaborate with cross-functional teams (Data Scientists, DevOps, Backend Engineers)
  • Monitor and evaluate LLM outputs for accuracy, safety, and bias
  • Stay updated with latest advancements in AI/ML and GenAI ecosystems

Required Skills

  • Strong programming skills in Python

  • Experience with Generative AI frameworks:

  • LangChain, LlamaIndex, Semantic Kernel

  • Hands-on experience with LLMs:

  • OpenAI GPT, Hugging Face, Llama, Mistral, etc.

  • Knowledge of prompt engineering techniques

  • Experience with vector databases

  • Familiarity with RAG architectures

  • Understanding of ML/DL fundamentals

  • Experience with REST APIs and microservices

Preferred Skills

  • Experience in fine-tuning LLMs (LoRA, PEFT, RLHF)
  • Knowledge of multi-modal models (text, image, audio)
  • Exposure to MLOps tools (MLflow, Kubeflow, Airflow)
  • Experience with cloud platforms (AWS, Azure, GCP)
  • Familiarity with Docker, Kubernetes
  • Understanding of data pipelines and big data tools
  • Knowledge of LLM evaluation frameworks

Tools & Technologies

  • Languages: Python, SQL
  • Frameworks: PyTorch, TensorFlow
  • GenAI Tools: LangChain, LlamaIndex
  • Databases: Pinecone, FAISS, ChromaDB
  • Cloud: AWS / Azure / GCP
  • DevOps: Docker, Kubernetes

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