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Metro Bangalore mid-level GenAI role with common title and 6+ years experience, high applicant density.
Specialized GenAI, LLM fine-tuning, and cloud MLOps require AI-focused backgrounds, moderately reducing cross-industry fit.
Explicit 6+ years and numerous mandatory GenAI, cloud, and MLOps skills create strict shortlisting filters.
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Build and deploy production-ready Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI solutions on GCP and Azure cloud platforms.
Design, develop, and optimize AI workflows including autonomous and multi-agent systems leveraging tools like LangGraph, LangChain, and prompt engineering.
Lead technical mentoring of junior AI/ML engineers and collaborate cross-functionally to support CI/CD, MLOps/LLMOps, and production AI service deployments.
6+ years of AI/ML engineering experience.
Strong proficiency in Python and AI frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Hands-on experience with GCP and Azure enterprise AI workloads, including Vertex AI and Gemini APIs.
Work Mode: Mandatory onsite work from office in Bangalore.
Experienced in building scalable AI solutions involving RAG, autonomous agents, and multi-agent systems in cloud environments.
Proficient in end-to-end AI solution deployment including containerization (Docker/Kubernetes), API integration, and MLOps pipelines with Azure DevOps or similar tools.
Comfortable leading cross-team collaboration and mentoring while managing complex AI deployments for enterprise customers.