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Strong employer brand, mid-level experience range, and Bangalore location increase candidate competition.
Role requires specialized generative AI/LLM expertise making industry transferability limited and domain-sensitive.
Explicit 4–7 years plus mandatory LLM, PyTorch, cloud, LangChain and CI/CD requirements make filtering strict.
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Design, develop, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Implement and optimize AI model pipelines with Python, PyTorch, Hugging Face Transformers, and LangChain; customize foundation models using domain-specific data.
Collaborate with data engineers and MLOps teams to productionize models on Azure, AWS, or GCP clouds and integrate GenAI capabilities into enterprise applications via APIs.
4 to 7 years of professional experience.
Bachelor of Technology (B.E/B.Tech) or Master's degree (M.Tech/MCA) in relevant fields.
Proficiency with Python, PyTorch, Hugging Face Transformers, and orchestration tools like LangChain.
Experience deploying AI solutions on cloud platforms such as Azure, AWS, or GCP; familiarity with ML pipeline tools like MLflow or Weights & Biases and CI/CD practices for ML (e.g., Azure ML or SageMaker Pipelines).
Has deep technical expertise and hands-on experience in cutting-edge Generative AI technologies and large language models.
Experience working in an Agile, product innovation or advisory environment with responsibility for end-to-end design and deployment of AI solutions at scale.
Comfortable collaborating across engineering and MLOps teams to ensure AI models are robust, scalable, compliant, and integrated into enterprise-grade applications.