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Specialized LLM/RAG skills reduce applicants, but generic 'Software Engineer' title increases competition.
Role requires specialized LLM, RAG, and vector DB expertise, making background fit highly domain-specific.
Many mandatory, niche ML/LLM skills and explicit 1-2 year requirement create strict filtering.
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Lead design, development, deployment, and iteration of AI-driven advertising agent features end-to-end in an Agile setup.
Implement, fine-tune, and optimize large language models (LLMs) and retrieval-augmented generation (RAG) systems integrated with vector databases for scalable AI solutions.
Own technical design documentation and collaborate across teams to align AI architectures with product strategies and customer needs.
1 to 2 years of professional experience working with LLMs and AI agent architectures.
Proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, and Hugging Face Transformers.
Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and agentic frameworks (LangGraph, CrewAI, AutoGen).
Work Experience Required: 1 to 2 years in AI/ML related development.
Has practical experience building AI agents featuring multi-agent orchestration, agent memory, tool-use, and observable agent systems for reliability and safety.
Demonstrates strong knowledge of prompt engineering, evaluation metrics for generative models, and fine-tuning techniques including small base model training.
Experienced in deploying AI models on cloud platforms and using containerization, with familiarity in programmatic advertising or ad auction mechanisms as a plus.