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Specialized GenAI role but metro location and mid-level experience increase applicant competition.
Highly domain-specific GenAI and LLMOps skills limit cross-industry transferability.
Multiple mandatory GenAI, LLMOps, cloud and MLOps skills plus explicit years requirement raise strictness.
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Design, build, and operationalize production-grade agentic AI systems automating marketing analytics workflows using LLMs and custom tools.
Own LLMOps/AIOps including prompt versioning, model rollout, cost/latency monitoring, drift detection, and automated regression testing.
Develop and maintain Retrieval-Augmented Generation pipelines, LLM evaluation frameworks, and MLOps practices across cloud platforms (AWS, GCP, Azure).
Minimum 4 years overall AI/ML experience with at least 2 years in Generative AI solutions.
Strong proficiency in Python and ML frameworks like PyTorch, TensorFlow, Scikit-learn.
Experience building and deploying LLM-based agentic AI systems, including RAG pipelines and LLM evaluation design.
Work Experience Required: At least 4 years in AI/ML, 2 years with Generative AI
Proven ability to deliver client-facing AI solutions with deep expertise in evaluation metrics and dataset curation for LLMs.
Experienced in implementing end-to-end Agentic AI SDLC including prompt engineering and tool-use prompting.
Skilled in cloud-native AI tools on Azure, AWS, or Snowflake and building production-ready GenAI MVPs with evaluation harnesses.