Principal Software Engineer

Overview

Lead the design, evolution, and reliability of AlphaSense's global financial data extraction and normalization platform, which ingests filings across formats and delivers trusted, traceable outputs at scale.

What you'll do

• Own the architecture and evolution of the large-scale data extraction and normalization platform.
• Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability.
• Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards.
• Establish clear system contracts for correctness, traceability, and confidence (e.g., "where did this number come from?").
• Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainability.
• Identify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity.
• Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary.
• Partner with product and downstream consumers to define quality bars, SLAs, and success metrics.
• Serve as a technical escalation point for production issues, reliability failures, and systemic risks.
• Mentor senior engineers, shape technical culture, and raise expectations for system design and execution.
• Contribute to long-term technical strategy while remaining hands-on with critical implementations.

What you'll need

• 15+ years of experience building and operating large-scale production systems.
• Proven experience designing data ingestion, extraction, or processing systems at scale.
• Deep expertise in one or more of: distributed systems; data platforms and pipelines; AI/ML-powered extraction or classification systems; platform or infrastructure engineering.
• Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches.
• Strong understanding of system reliability, observability, failure modes, and iterative hardening.
• Experience reducing operational or human overhead through better system design.
• Track record of technical leadership across teams without formal people management.
• Comfortable operating in ambiguity and driving clarity where none exists.
• Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems.

Nice to have

• Experience with document understanding, NLP, or financial data extraction.
• Experience building provenance, lineage, or confidence-scoring systems.
• Familiarity with cloud-native architectures and modern data stacks.
• Experience shaping or owning internal platforms used by multiple teams.

Details

• Location: Remote, United States.
• Compensation range: $246,000 to $339,000 USD, plus possible equity and a benefits program.