Job description
Builds and ships production AI features for client products: retrieval-augmented generation pipelines, agents, and copilots that move real workflows.
What you'll do
- Design, build, and deploy LLM-powered applications, agents, and copilots for client products
- Build retrieval-augmented generation (RAG) pipelines and vector database integrations
- Integrate large language model APIs into production systems with attention to cost and latency
- Write evaluation harnesses to measure model quality before and after shipping
- Work directly with client and product teams to turn business requirements into working AI features
- Monitor deployed AI systems for drift, cost overruns, and reliability issues
Skills
- 3+ years of professional software engineering experience, including 1+ years building LLM-based applications
- Strong Python and working knowledge of LangChain, LlamaIndex, or a comparable orchestration framework
- Experience with a vector database (Pinecone, Weaviate, pgvector, or similar)
- Solid understanding of prompt design, RAG architecture, and evaluation methods
- Comfortable working directly on AWS, Azure, or GCP