Principal + Staff Software Engineers, Unstructured

• Have 10+ years of software engineering experience with a focus on distributed systems, infrastructure, or data architecture
• Are a Python expert—capable of building frameworks and performance-critical services from scratch
• Have deep Kubernetes expertise; you can design, deploy, and debug at scale and could teach others how to productionize it securely
• Are fluent in Postgres—you understand query planning, partitioning, and tuning for high-throughput environments
• Are obsessed with clean, scalable architecture and can lead design reviews that shape how entire systems evolve
• Have experience in high-performance data or AI/ML systems—especially those involving retrieval pipelines, embeddings, or hybrid workloads
• Thrive in fast-moving, ambiguous environments where technical depth and judgment matter more than process

Desirable

• 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
• 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