Principal Software Engineer
Posted Updated
- We are seeking a Principal Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform
- This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers
- This role owns the self-sourcing and extraction foundation used by multiple teams across the organization
- Today, human validation is used as a safety net
- Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability
- You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems
- Own the architecture and evolution of our 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 explainabilityIdentify 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
Benefits
- Work from home opportunities
- Strong understanding of system reliability, observability, failure modes, and iterative hardening
- Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
- Deep expertise in one or more of:
- Platform or infrastructure engineering
- Data platforms and pipelines
- Track record of technical leadership across teams without formal people management
- Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems
- Distributed systems
- Proven experience designing data ingestion, extraction, or processing systems at scale
- AI/ML-powered extraction or classification systems
- Comfortable operating in ambiguity and driving clarity where none exists
- Experience reducing operational or human overhead through better system design
- 15+ years of experience building and operating large-scale production systems
- Experience with document understanding, NLP, or financial data extraction
- Experience building provenance, lineage, or confidence-scoring systems
- Experience shaping or owning internal platforms used by multiple teams
- Familiarity with cloud-native architectures and modern data stacks
