Staff Software Engineer

AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance. The platform combines domain-specific AI with a vast content universe of over 500 million premium business documents — including equity research, earnings calls, expert interviews, filings, news, and internal proprietary content. Purpose-built for speed, accuracy, and enterprise-grade security, AlphaSense helps teams extract critical insights, uncover market-moving trends, and automate complex workflows with high-quality outputs. With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly. For more information, visit www.alpha-sense.com. Come join us.

We are seeking a Staff Software Engineer to join Reference and Entity Data Systems (REDS) and own the design and evolution of our entity data platform — ingesting company data from global vendors, resolving it into authoritative records, and delivering accurate, timely data to downstream teams and customers. REDS owns vendor ingestion, entity generation, data quality and freshness, and delivery to downstream consumers.

If entity data is wrong, incomplete, or stale, everything downstream fails. Human validation still acts as a safety net in parts of the pipeline. Your mission is to systematically reduce that dependency by increasing correctness, confidence, and trust — without sacrificing speed or scale.

You will operate at the intersection of distributed systems, entity resolution, data quality, AI-assisted decision-making, and platform architecture.

• 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
• Experience evolving or re-platforming live systems with many downstream consumers

• 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

• →Own the architecture and evolution of a major area of the entity data platform
• →Design systems that ingest and serve large volumes of heterogeneous vendor data at scale 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