Search & AI Retrieval Lead at proSapient

Join proSapient as a Staff-level IC to define the future of information discovery. You will architect a next-generation hybrid Graph RAG and GNN reranker system, partnering closely with Google’s product teams. This high-impact role balances hands-on Python development with strategic architectural guidance to surface insights across massive, unstructured datasets for global investors.

• Architect and implement a scalable, cloud-native search stack on GCP, deciding between and combining vector search, hybrid retrieval, and graph-based approaches.
• Design and implement a Knowledge Graph architecture that models complex entities and relationships, integrating extraction pipelines powered by frontier models like OpenAI and Gemini.
• Develop production-grade intelligent retrieval systems and recommendation engines that leverage both structured and unstructured data to surface the world’s most niche expertise.

• Possesses 5+ years of experience building and scaling production search or retrieval systems, with a strong background in Python and cloud-native architecture on GCP.
• Demonstrates deep expertise in semantic search, embeddings-based retrieval, and building production-grade data pipelines on top of frontier LLMs like OpenAI and Gemini.
• Proven ability to lead technical initiatives and design complex architectures, with specific experience in knowledge graphs, entity linking, and re-ranking strategies at scale.

• Build a cutting-edge hybrid Graph RAG + GNN reranker system in direct partnership with Google’s product teams, ensuring you stay at the absolute frontier of retrieval technology.
• Join a high-motivation, low-ego environment with 0% politics where you report directly to the CTO as a Staff-level individual contributor with 70% hands-on work.
• Work with genuinely unique data spanning every imaginable business sector, from deep tech to agriculture, creating systems that directly impact multi-million dollar investment decisions.