Solutions Engineer — RAG

Pinecone is looking for a Solutions Engineer specializing in Retrieval-Augmented Generation (RAG) to serve as a technical advisor for our strategic enterprise accounts. In this role, you will bridge the gap between complex vector database technology and real-world business outcomes by designing production-grade AI architectures. You will work directly with engineering teams at world-class companies to optimize their search relevancy, reduce latency, and scale their AI infrastructure to billions of embeddings.

- Lead technical discovery sessions and architectural reviews to design scalable RAG systems for Pinecone's largest customers. - Develop custom proof-of-concepts (PoCs) and reference architectures demonstrating advanced techniques like hybrid search and reranking. - Partner with the Product and Engineering teams to feed back customer requirements into the Pinecone roadmap. - Troubleshooting complex indexing and query performance issues in high-throughput production environments. - Create technical content, including blog posts, notebooks, and webinars, to educate the developer community on vector database best practices. - Act as the primary technical point of contact during the pre-sales and onboarding phases for strategic accounts. - Conduct performance benchmarking and cost-optimization exercises for customers moving from prototype to global scale.

- 5+ years of experience in a customer-facing technical role such as Solutions Architecture, Sales Engineering, or Developer Relations. - Proven expertise in natural language processing (NLP) and familiarity with LLM orchestration frameworks like LangChain or LlamaIndex. - Deep understanding of vector search concepts including HNSW, IVF, cosine similarity, and dot product metrics. - Hands-on experience building and deploying RAG pipelines in production environments using Python or Node.js. - Strong knowledge of cloud infrastructure (AWS, Azure, or GCP) and managed Kubernetes environments. - Exceptional communication skills with the ability to explain high-dimensional mathematical concepts to both developers and C-suite executives. - Experience with traditional search technologies (Elasticsearch, Solr) or SQL/NoSQL databases at scale.