AlphaSense is a company that provides AI-driven market intelligence to help professionals make informed decisions. They are seeking a Staff Software Engineer to own the design and evolution of their entity data platform, focusing on data ingestion, resolution, and quality to ensure accurate and timely data delivery to users.
Responsibilities:
- Own the architecture and evolution of a major area of the entity data platform
- Design systems that process large volumes of heterogeneous vendor data with high reliability, freshness, and accuracy
- Reduce manual validation overhead through AI-assisted resolution, confidence scoring, provenance, and deterministic matching rules
- Establish clear contracts for correctness and traceability — e.g., which source supplied a field, why an entity was matched or created
- Balance AI-driven and rules-based approaches where each improves reliability and explainability
- Deliver end-to-end integrations across ingestion, matching, entity generation, and delivery
- Respond to production incidents in your area; improve observability and reliability through iterative hardening
- Set engineering standards, mentor engineers, and partner with product and downstream consumers on quality bars and success metrics
Requirements:
- 8+ years building and operating large-scale production systems
- Proven experience with data ingestion, entity resolution, matching, or normalization at scale
- Deep expertise in one or more of: distributed systems, data pipelines, reference data platforms, platform engineering, or AI-powered classification and validation
- Strong code, system design, and architecture pattern skills
- Ability to design trustworthy systems combining probabilistic (AI) and deterministic approaches
- Delivery excellence: incident response, observability, and reliability improvements that stick
- Effective use of AI, testing, automation, and tooling to ship confidently
- Track record of setting standards, driving technical decisions, and elevating peers through documentation and mentoring
- End-to-end ownership from integration through entity generation to operational readiness
- Experience with company or financial reference data, or vendor reconciliation
- Provenance, lineage, confidence-scoring, or quarantine/resolution workflows
- Integrating new data vendors end to end
- Cloud-native architectures and internal platforms shared across teams