Software Development Engineer - Tejas

Enterprises want agents that can do real work on their own data. That data sits across documents, databases and business systems that were never built for agents to read, and today's agents forget most of what they learn once a session ends.

Our team builds Sarvam's context engine to solve both problems. The knowledge side brings an enterprise's data together so agents can search it, navigate it and cite where an answer came from. The memory side lets agents remember what they learn over time, about individual users, about teams, and across the organisation. We want both to keep improving as they are used.

Knowledge and memory for agents is a rapidly evolving field. We want to build at the frontier of it, and to show with measurable results that our approach does better than traditional ones.

• Build and run the ingestion pipeline that parses, extracts and indexes large volumes of documents, and keep it reliable when files are messy and external services fail.