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Strong employer brand, Bengaluru metro, popular AI title, and broad GenAI requirements raise competition.
ML/GenAI skills transfer across industries, but enterprise life-sciences context increases domain preference.
Explicit 0–2 years and multiple mandatory GenAI, MLOps, and cloud skills impose moderate strictness.
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Design, develop, deploy, and monitor AI/ML models including Generative AI and Agentic AI frameworks for production use.
Build AI solutions using prompt engineering, RAG, multimodal AI, and autonomous reasoning integrated into business applications on Azure.
Develop and maintain data and MLOps pipelines, model versioning, and BI dashboards with tools like Snowflake, Power BI, and Tableau.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.
0–2 years of relevant AI/Data Engineering experience required.
Strong programming skills in Python, Java, or C# with experience in AI libraries such as TensorFlow or PyTorch.
Experience with Generative AI (LLMs), Agentic AI systems, and AI frameworks like LangChain, Hugging Face, or OpenAI APIs.
Familiar with deployment and monitoring of AI models on cloud platforms, especially Azure, and associated monitoring tools (Azure Monitor, Grafana, Prometheus).
Capable of integrating AI into real-time business applications and building scalable AI-driven solutions.
Experienced with AI-assisted coding agents and comfortable collaborating across data science, software engineering, and product teams.