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Senior, specialized GenAI role but metro location and attractive title increase applicant density.
Highly specialized Databricks and LLMOps requirements reduce cross-industry transferability.
Explicit 8+ years requirement and numerous mandatory LLMOps, Databricks, and cloud skills.
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Design and deploy advanced machine learning and AI solutions, including LLM-based and agentic AI systems, to solve complex business problems with measurable outcomes.
Lead production deployment, operation, and scaling of AI/ML and GenAI models on cloud platforms (Azure, AWS, GCP) and within the Databricks ecosystem.
Establish and manage MLOps/LLMOps best practices, develop RAG architectures, embeddings, vector databases, and ensure responsible AI and security compliance.
Minimum 8 years of experience in AI/ML engineering, machine learning, data science, or related fields.
Advanced programming skills in Python and proficiency in SQL with experience handling large structured and unstructured datasets.
Proven hands-on experience deploying LLM-based applications, agentic AI systems, and production AI/ML or GenAI models on Azure, AWS, or GCP.
Bachelor's degree in Computer Science, Data Science, AI, IT or closely related field; certifications in machine learning, AI engineering, or cloud platforms preferred.
Experienced in architecting and scaling enterprise-grade autonomous AI agent platforms using Databricks and cloud-native tools.
Demonstrates practical expertise in MLOps/LLMOps across multi-cloud environments with focus on model lifecycle management and CI/CD automation.
Skilled in advanced LLM technologies including prompt engineering, vector search, embeddings, and robust AI security to ensure reliable production AI solutions.