Principal/Senior/Software Engineer, AI-Powered Advertising Agents - AgenticOS

What you'll do

• Lead design, development, and deployment of AI-driven features with end-to-end ownership
• Spearhead technical design meetings and produce detailed design documents for scalable, secure AI architectures
• Align solutions with long-term product strategy and technical roadmaps
• Implement and optimize LLMs including fine-tuning, deploying pre-trained models, and evaluating performance
• Develop AI agents powered by RAG systems integrating external knowledge sources
• Design, implement, and optimize vector databases for efficient and scalable vector search
• Create and fine-tune sophisticated prompts to improve LLM performance
• Utilize evaluation frameworks and metrics to assess and improve generative models and AI systems
• Collaborate with data scientists, engineers, and product teams to integrate AI capabilities into products and tools
• Stay updated with latest research and trends in LLMs, RAG, and generative AI
• Continuously monitor and optimize models for performance, scalability, and cost efficiency

Requirements

• 2 to 10 years of experience and strong understanding of LLMs and their underlying principles — transformer architecture, attention mechanisms, and hyperparameter tuning
• Proven experience designing and building AI agents, including multi-agent orchestration, tool-use patterns, multi-step planning, and agent memory architectures
• Hands-on experience with agentic frameworks such as LangGraph, CrewAI, or AutoGen, and familiarity with RAG pipelines integrating external knowledge sources
• In-depth knowledge of vector databases and indexing algorithms; practical experience with FAISS, Pinecone, Weaviate, or Milvus
• Experience with agent observability, tracing, and guardrails using tools like Langfuse or equivalent
• Proficiency in prompt engineering for context-sensitive, domain-specific LLM outputs
• Familiarity with Evals and other performance evaluation tools
• Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers
• Experience with data preprocessing, vectorization, and handling large-scale datasets
• Ability to present complex technical ideas and results to both technical and non-technical stakeholders
• Bachelor’s degree in engineering or equivalent from a well-known institute/university

Tech stack

Benefits