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Strong Big Four brand, mid-level 4–7 years, metro Bengaluru, and broad GenAI skillset drive high competition.
Specialized GenAI and LLM expertise increases domain bias, though Python and cloud skills are transferable.
Mandatory 4–7 years and specific GenAI, PyTorch, LangChain, cloud and ML pipeline experience raises strictness.
Design, develop, and deploy scalable Generative AI solutions using large language models and transformer architectures.
Fine-tune models and optimize prompt engineering for accurate, context-aware AI responses.
Collaborate with data engineering and MLOps teams to productionize AI models on Azure, AWS, or GCP cloud platforms with compliance and scalability.
4 to 7 years of work experience in relevant fields.
Proficiency in Python, PyTorch, Hugging Face Transformers, and Generative AI (LLMs, Transformers).
Experience with cloud platforms Azure, AWS, or GCP and orchestration frameworks like LangChain or Langgraph.
Bachelor of Technology degree (B.E/B.Tech) or equivalent in engineering or technology.
Experienced in full lifecycle AI model deployment and integration into enterprise-scale systems on cloud platforms.
Skilled in deploying and managing ML pipelines, including CI/CD practices using Azure ML or SageMaker Pipelines.
Able to implement advanced AI techniques such as agentic AI and Retrieval-Augmented Generation (RAG) with familiarity of vector databases and API development.