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Mid-level GenAI role in Bangalore with broad LLM skillset attracts many qualified applicants.
LLM and ML engineering skills are transferable, advisory context adds moderate domain specificity.
Multiple mandatory technical skills, cloud and ML pipeline experience, and tool-specific requirements increase filtering rigor.
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Design, develop, and deploy scalable generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures.
Implement and optimize prompt engineering, model workflows, and AI integrations within enterprise systems on cloud platforms such as Azure, AWS, or GCP.
Collaborate with data engineers and MLOps teams to productionize AI models using orchestration frameworks like LangChain and manage ML pipelines with tools such as MLflow or Weights & Biases.
3 to 5 years of relevant experience in generative AI engineering or related fields.
Proficiency in Python, PyTorch, and Hugging Face Transformers.
Experience with cloud AI platforms on Azure, AWS, or GCP, including ML pipeline tools and CI/CD practices.
Bachelor's degree required: B.E / B.Tech / M.Tech / MCA; MBA explicitly required as degree/field of study in the JD.
Experienced in deploying foundation LLMs like OpenAI, Anthropic, or open-source models (LLaMA, Falcon) and customizing them with domain-specific datasets.
Skilled in using orchestration frameworks (LangChain, Langgraph) and API development (FastAPI, Flask) to integrate AI into enterprise environments.
Familiar with production-level AI system requirements including robustness, scalability, and compliance on major cloud platforms.