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Unstructured Technologies Inc.
Remote
Source: Unstructured Technologies Inc. careers · View original posting
From Unstructured Technologies Inc.'s posting. “We” and “our” refer to the employer.
Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we've raised over $65M from world-class investors, including Menlo Ventures, Bain Capital, Databricks, NVIDIA, Microsoft, and IBM.
Our open-source toolkit has been downloaded 97M+ times and is used by 90% of the Fortune 1000. We power production AI workflows across commercial and federal sectors — transforming PDFs, HTML, Word docs, images, emails, and more into AI-ready data pipelines that scale.
We're not just building tools; we're building the backbone of generative AI and the infrastructure that unlocks intelligence across industries.
Unstructured is looking for Staff and Principal Software Engineers to define the architectural foundation for how enterprises process and transform unstructured data for large-language-model (LLM) applications.
This is a high-impact, hands-on role for someone who thrives in deep systems work—someone who could write the book on Kubernetes, lives and breathes Python, and understands Postgres at the index and transaction-log level. You’ll own the technical direction for our core platform, guiding how data moves through every layer—from ingestion to transformation to retrieval.
You’ll partner closely with the Head of Engineering, Head of Infrastructure, and product leaders to ensure Unstructured’s systems are performant, resilient, and ready to support the next generation of AI-driven workloads.
Location(s) Preferred: San Francisco, Bay Area, San Jose, Seattle, Sacramento
Define and evolve the end-to-end architecture for Unstructured’s data transformation and retrieval platform.
Build and scale distributed systems that process massive volumes of unstructured data across diverse formats and sources.
Serve as the company-wide authority on Kubernetes orchestration, cluster design, performance tuning, and reliability.
Lead Python architecture and best practices—ensuring performance, modularity, and maintainability across services.
Design and optimize Postgres schemas, queries, and indexing strategies to support large-scale metadata and retrieval pipelines.
Mentor senior engineers through design reviews and code guidance, raising the bar for technical excellence across the org.
Partner with the infrastructure and product teams to translate research prototypes into production-grade systems.
Evaluate emerging technologies and open-source tools in LLM infrastructure, retrieval, and orchestration—deciding where and how to integrate them.
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