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Remote role, metro hiring, mid-level (5+ yrs), and broad AI/LLM skillset increase competition.
Core ML, MLOps, and cloud skills transfer across industries, though specialized LLM/agent experience narrows fit.
Explicit 5+ years and 2+ years Generative AI production experience plus specific tech stack required.
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Design, develop, deploy, and optimize scalable AI/ML solutions including Generative AI and LLMs for complex business challenges.
Collaborate with AI data scientists, architects, and engineers to deliver AI-driven solutions ensuring security, scalability, governance, and operational excellence.
Build and maintain MLOps pipelines, cloud-native AI applications, and enterprise integrations primarily on AWS, Azure, or Google Cloud.
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 with at least 2 years in production deployment of Agentic AI, Generative AI, or AI/ML solutions.
Strong programming skills in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, LangChain, and relevant cloud AI services (AWS, Azure, Google).
Experience with MLOps tools and practices including MLflow, Kubeflow, Docker, Kubernetes, and CI/CD automation; Location: India-Bangalore (Remote).
Experienced in designing enterprise-scale AI platforms and production-grade AI applications incorporating Generative AI, LLMs, and multi-agent AI systems.
Comfortable operating in cloud environments (AWS preferred) with strong MLOps and DevOps skills to ensure operational AI solution reliability.
Knowledgeable in AI governance, Responsible AI frameworks, security, and compliance for deploying secure and explainable AI systems.