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Mid-level GenAI role in metro with moderate brand recognition and specialized skill requirements, attracting moderate competition.
Specialized ML/LLM and MLOps skills are transferable across industries but favor AI-focused teams.
Multiple mandatory ML/LLM, MLOps, and cloud technology requirements increase filter rigidity.
Design, develop, test, and deploy scalable AI/ML and generative AI solutions including LLM applications and RAG solutions to improve business outcomes.
Build and optimize data pipelines supporting AI model training and inference; create scalable APIs and AI services for enterprise use.
Implement MLOps best practices, validate agentic AI outputs, ensure solution compliance with security and responsible AI standards, and collaborate with cross-functional teams to translate requirements into AI solutions.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
Strong programming skills in Python and SQL; experience with Large Language Models (OpenAI, Anthropic, Llama) and prompt engineering.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform; knowledge of REST APIs, Git, and software development best practices.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in deploying and managing AI-powered applications with expertise in Large Language Models and prompt engineering.
Skilled in building scalable data pipelines and APIs, with familiarity in MLOps, agentic AI testing, and AI governance standards.
Operates effectively in cross-functional teams translating business needs into AI solutions, with knowledge of modern data platforms like Snowflake and Databricks, and AI orchestration frameworks (LangChain, LangGraph, Semantic Kernel).