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Remote role, Bangalore metro, mid-level seniority, and popular AI/LLM title increase candidate competition.
Specialized LLM, MLOps, and cloud skills moderately limit transferability across non-AI industries.
Explicit 5+ years plus 2+ years LLM production experience, MLOps, cloud, and toolchain requirements make filters strict.
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Design, develop, deploy, and optimize scalable AI and Machine Learning solutions including Generative AI, LLMs, and agentic workflows for complex business problems.
Build and maintain production-grade AI applications and APIs integrating AI services with enterprise systems using Python and cloud platforms (AWS preferred).
Implement MLOps pipelines for model lifecycle management, monitoring, and operational excellence while ensuring AI governance, security, and compliance.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related technical field.
Minimum 5 years of software engineering or machine learning development experience; 2+ years hands-on in production deployment of Generative AI or AI/ML solutions.
Strong expertise in Python programming and experience with cloud AI services on AWS, Azure, or Google Cloud.
Experience with AI model development frameworks (PyTorch, TensorFlow), MLOps tools (MLflow, Kubeflow), and CI/CD practices.
Experienced AI engineer capable of designing and deploying enterprise-scale AI/ML platforms with deep knowledge of Generative AI, LLMs, and agentic AI.
Comfortable working in highly technical, cross-functional teams involving data scientists, architects, and cloud engineers in a remote setup.
Demonstrated ability to apply AI governance, Responsible AI frameworks, and secure AI system design in compliance-driven environments.