Build AI-Enabled Products: Develop products that are fully enabled by the capabilities of LLMs and other recent developments in foundation models. You will evaluate and assimilate emerging techniques into our production systems.
High-Performance Search and RAG: Build and optimize our data indexing, ranking, and query processing systems for high-performance Search and Retrieval-Augmented Generation (RAG).
Develop Evaluation Frameworks: Create robust frameworks to evaluate the performance of our agents, RAG systems, and various LLMs. We take a polyglot approach to working with LLMs, with a strong preference for getting workloads running on open-source models.

1-3 years of experience in Software Engineering or end-to-end Data Science
Strong proficiency in Python and data-oriented algorithms.
Strong background in either distributed AI agents, data systems or machine learning engineering.
Modern Python microservices with FastAPI, Ray.IO for distributed AI workloads, and Kubernetes orchestration
powering enterprise-scale AI agent execution with gRPC inter-service communication and Google Cloud Pub/Sub event streaming
AI Agent Stack: LlamaIndex, LangGraph, SmolAgent, Instructor, Anthropic, OpenAI, Qdrant, ParadeDB, Sentence-Transformers, FAISS
building sophisticated AI agent orchestration with tool coordination, vector search, and real-time data processing
Recent demonstrated experience in building agents, training and evaluating emerging LLMs, building RAG systems, or working with vector databases. We encourage you to share your projects with us!
Familiarity with our core technologies is a plus: Ray, Postgres, Iceberg, Google Cloud, and Docker/Kubernetes/Helm.

AI Engineer

Key skills