Description

You will design and deploy AI agents and LLM-driven features for advertising systems, owning the full lifecycle from technical design to release.

This role is remote.

Responsibilities

• Lead the design, development, and deployment of AI agents using RAG systems, vector databases, and graph-based architectures.
• Fine-tune and optimize LLMs, implementing prompt engineering strategies and evaluation frameworks to improve accuracy and cost efficiency.
• Build scalable vector search solutions using algorithms and tools like FAISS, Pinecone, or Weaviate.
• Collaborate with product and data teams to integrate generative AI capabilities into customer-facing products and internal tools.
• Produce detailed technical design documents and mentor engineering teams on AI architecture best practices.

Required Skills

• 5+ years of experience with Python, Machine Learning, and LLM principles (transformers, attention mechanisms, hyperparameter tuning).
• Proven experience building AI agents, including multi-agent orchestration, tool-use patterns, and memory architectures.
• Hands-on experience with LangGraph, CrewAI, or AutoGen frameworks.
• Deep knowledge of RAG systems, vector databases (FAISS, Pinecone, Weaviate, Milvus), and prompt engineering.
• Proficiency with TensorFlow, PyTorch, and Hugging Face Transformers.
• Experience with containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
• Understanding of agent observability tools like Langfuse and graph neural networks.

Preferred Skills

• Experience with programmatic advertising, RTB, or ad auction mechanics.
• Familiarity with MCP (Model Context Protocol) or similar tool-integration standards.

Key Skills

Education

Any Graduate