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Staff Software Engineer

Condor Software
CompanyCondor Software
CategoryEngineering
LocationSan Francisco
RemoteHybrid
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted3 Feb 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
ABOUT CONDOR Every year, hundreds of billions of dollars are invested to discover and develop new therapies, yet the financial infrastructure behind that work has not kept pace. Clinical operations and finance live in disconnected worlds, forcing teams to make high-stakes decisions using fragmented tools and static data. Condor exists to change that. We are a system of action, building the financial intelligence layer that will power the next era of clinical development. Condor connects clinical operations, vendor activity, and financial signals into a single, real-time intelligence layer, giving R&D and finance leaders true command over how their organizations operate. Condor is pharma-native, AI-driven infrastructure built to scale industry standards we helped define with Big 4 partners. It powers prediction, control, and execution across the most complex R&D environments in the world. WHY THIS MATTERS NOW Condor has moved past proving the concept. Enterprise teams already trust Condor to run critical operations and finance. The work ahead is the hardest part: scaling something people depend on when the stakes are this high. Condor is a high-growth company backed by top institutional partners like Felicis and 645 Ventures, growing rapidly with Top 200 biopharma companies. This is a rare opportunity to help build foundational infrastructure that will shape how new therapies reach patients. THE ROLE We are looking for a Staff Software Engineer, Backend & Data to set the technical direction for the core data infrastructure behind Condor's financial intelligence platform. This role sits at the heart of how Condor turns complex clinical and financial activity into intelligence that enterprise biopharma teams trust to run their operations. You will design and own the data foundations that power Condor's financial engine and AI-driven capabilities. That means modeling highly complex, high-stakes data, building reliable pipelines and services, and ensuring that downstream product features and intelligence workflows operate with accuracy, consistency, and scale. As a Staff engineer, you will drive architectural decisions that span multiple teams and establish the patterns others build on. The systems you shape will directly support mission-critical finance and operational use cases, not dashboards or experiments. This is a hands-on, high-leverage role with broad technical ownership. You will work across backend services, data pipelines, and APIs, taking the hardest problems from design through production, while raising the bar for how the wider engineering organization models, moves, and serves data. You will help define the schemas, transformations, and architectural patterns that become the backbone of the platform as it scales. While the primary focus is backend and data engineering, you are expected to engage pragmatically across the stack—including machine learning and AI systems—to ensure data and intelligence are surfaced correctly in the product. This role is for engineers who want to build durable infrastructure under real-world complexity, where correctness, trust, and scale are not optional, and where the systems you design will shape how an entire industry operates. KEY RESPONSIBILITIES - Set technical direction for Condor's data platform, driving cross-team architectural decisions on data modeling, storage strategies, and integration with LLMs, embeddings, and vector databases. - Design, build, and maintain scalable data pipelines that ingest, normalize, and transform financial and clinical trial data from multiple internal and external sources, with a focus on making data suitable for analytics, reporting, and LLM-based AI agents. - Develop backend services and data access layers that expose high-quality financial data to internal systems and customer-facing features, ensuring data is structured for direct consumption by LLMs and automated workflows. - Implement and operate embedding pip
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