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Mid-level GenAI role in Bangalore at a well-known firm with broad appeal and metro location increases applicant competition.
Core GenAI engineering skills transferable, but domain-specific LLM and enterprise deployment experience raises moderate sensitivity.
Explicit 4–7 year requirement and many mandatory GenAI tool and cloud skills make filters strict.
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Design, develop, and deploy scalable Generative AI solutions using large language models (LLMs) and transformer architectures.
Build and optimize intelligent applications, including model orchestration workflows and API integrations, on cloud platforms (Azure, AWS, GCP).
Collaborate with data engineers and MLOps teams to productionize GenAI models ensuring robustness, scalability, and compliance.
4 to 7 years of work experience in Generative AI or related roles.
Bachelor's degree in Technology or Engineering (B.E/B.Tech) or Master's in Technology or MCA.
Proficient in Python, PyTorch, Hugging Face Transformers, and LangChain or similar orchestration frameworks.
Experience deploying AI/ML solutions on cloud platforms like Azure, AWS, or GCP; familiarity with CI/CD pipelines for ML using tools such as Azure ML or SageMaker Pipelines.
Skilled in fine-tuning and customizing foundation models with domain-specific data and prompt engineering.
Experienced in managing ML pipelines and production environment integrations for enterprise-grade GenAI applications.
Capable of leveraging orchestration frameworks and cloud AI platforms to deliver scalable, compliant, and high-performing Generative AI solutions.