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Strong employer brand, mid-level experience band, and Bangalore metro location increase candidate competition.
Technical GenAI skills are highly transferable across industries, indicating low background bias.
Explicit 4–7 years and many mandatory GenAI, ML frameworks, cloud, and CI/CD skills increase shortlisting strictness.
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Design, develop, and deploy scalable Generative AI solutions using large language models and transformer architectures.
Build and optimize model pipelines and integrate GenAI capabilities into enterprise systems on cloud platforms (Azure, AWS, GCP).
Collaborate with data engineers and MLOps to productionize models, ensuring robustness, scalability, and compliance in deployment.
4 to 7 years of relevant work experience.
Bachelor's degree in Engineering (B.E/B.Tech) or equivalent (M.Tech/MCA also acceptable).
Strong expertise in Python, PyTorch, Hugging Face Transformers, LangChain or similar, and cloud platforms Azure, AWS or GCP.
Experience with ML pipeline tools (MLflow, Weights & Biases), REST API development (FastAPI or Flask), and CI/CD for ML (Azure ML, SageMaker pipelines).
Experienced in fine-tuning and customizing foundation models using domain-specific data and prompt engineering.
Familiar with agentic AI implementation and orchestration frameworks like LangChain/Langgraph, indicating a strategic understanding of AI workflows.
Comfortable working in multi-cloud environments integrating GenAI into enterprise applications with emphasis on scalable and compliant production deployment.