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Mid-level AI role with popular title but niche LLM/embedding requirements reduces applicant density.
Core ML/LLM skills are broadly transferable across industries, so background fit sensitivity is low.
Explicit 4+ years requirement plus mandatory LLM, embedding, and agentic AI skills increases filter strictness.
Design, develop, and maintain scalable AI workflows and embedding pipelines handling structured and unstructured data.
Implement semantic search solutions, AI-driven summarization, analytics, and insight generation over structured datasets.
Integrate and optimize Large Language Models (LLMs) and develop Agentic AI systems for multi-step reasoning and autonomous workflows, ensuring production-readiness including performance and cost optimization.
Minimum 4 years of strong Python development experience building production-grade systems.
Hands-on experience with LLM integration (e.g., OpenAI APIs, Anthropic, open-source), embedding models, and vector search pipelines.
Experience with AI summarization, insight extraction, and Agentic AI architectures (multi-agent systems, tool calling, workflow automation).
Strong knowledge of data processing frameworks such as Pandas and NumPy.
Technically proficient in advanced AI workflows, LLM integration, and production-grade AI system development.
Experienced in designing end-to-end AI solutions collaborating with data engineers and product teams.
Skilled in optimizing AI model performance, prompt engineering, and deployment for real-world applications.