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Raven is a YC-backed startup building AI for heavy industries. We’re building Cursor for industrial work — data infrastructure for process plants and AI agents that work on top of this data. We work with manufacturing, chemicals, oil & gas, and other industrial teams to help engineers access, understand, and act on complex plant information faster. We’re a small, focused team based in Bangalore, building for teams that work in some of the toughest operational environments.
Job Responsibility
Building the plant data/model layer that brings together P&IDs, SOPs, datasheets, historian data, maintenance records, logs, and other plant context
Building pipelines to extract structured, reliable data from industrial documents and systems
Making plant data usable by AI agents with grounding, traceability, and review workflows
Building Python/Go backend services for data ingestion, search, orchestration, and agent workflows
Working on knowledge graphs, entity resolution, event timelines, and plant topology
Building agents that work on top of this data to help engineers answer questions, investigate issues, and execute operational workflows
Working directly with customers to understand real plant workflows and turn them into shipped product
Requirements
2–4+ years of experience building production backend systems
Strong Python and/or Go skills
Experience building APIs, services, data pipelines, or backend infrastructure
Ability to own technical problems end-to-end and ship working systems
Comfortable working in ambiguity, iterating fast, and solving real customer problems
Nice to have
Experience with AI systems, document extraction, search/retrieval, workflow automation, or evaluation pipelines
Interest in industrial data like P&IDs, SOPs, datasheets, historian data, and maintenance records
Interest in knowledge graphs, entity resolution, traceability, and grounded AI outputs
Startup experience or experience working in small, high-ownership teams
Comfortable working directly with customers and wearing multiple hats
What we offer
0.1–1% equity
Impact: work on real-world industrial problems where better systems can improve safety, reliability, and efficiency
Depth: work across backend systems, data pipelines, document intelligence, plant data, and AI agents