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Mid-level GenAI/ML role, popular title, metro location, broad skillset requirements create high applicant density.
Specialized GenAI and platform skills moderate transferability across industries.
Multiple mandatory technical stacks, explicit years and LLM experience make filters highly strict.
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Design, build, and deploy secure, scalable generative AI and agentic AI solutions including LLM-based systems for domain-specific enterprise use cases.
Develop and operate Azure-based data pipelines using Databricks, ADF, and Delta Lake architectures to support analytics and ML workflows.
Lead architecture and deployment of ML solutions at scale, integrate advanced AI into workflows, and oversee model safety, evaluation, and operationalization.
5–6 years of professional experience in software engineering and AI-related roles.
Minimum 2–3 years of direct experience with Generative AI and Large Language Models (LLMs).
Proficiency in Python, ML/AI libraries (TensorFlow, PyTorch, scikit-learn), and experience with Azure cloud data platforms and tools.
Location requirement: Pune, Maharashtra, India.
Experienced in architecting and operationalizing enterprise-scale generative AI workflows, including multi-step agentic AI orchestration and LLM red-teaming.
Skilled in designing robust, production-grade data pipelines using Azure Data Factory and Databricks following medallion architecture best practices.
Capable of translating complex business requirements into scalable AI/ML technical solutions with emphasis on performance, security, and compliance.