Design, build, and iterate on AI-powered features — from prototype to production Develop and maintain LLM-based pipelines including RAG systems, agents, and prompt engineering frameworks Fine-tune, evaluate, and benchmark models for domain-specific tasks Build robust backend APIs and microservices that serve AI capabilities at scale Collaborate with product and design to translate AI capabilities into intuitive user experiences Integrate third-party AI services (OpenAI, Anthropic, Cohere, HuggingFace, etc.) and manage their trade-offs Instrument AI systems with monitoring, logging, and evaluation metrics to track quality over time Contribute to internal tooling, reusable components, and best practices for AI development
AI / ML: LLM APIs & prompt engineering RAG pipelines & vector databases Model fine-tuning (LoRA, PEFT) Evaluation frameworks & evals design Familiarity with ML frameworks (PyTorch / HuggingFace) ENGINEERING: Python (primary) + one other language REST APIs & async bac...