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AlphaSense is seeking an experienced Senior Platform Engineer to work on the search platform powering market intelligence across billions of documents. The role focuses on building and optimizing distributed systems that handle hundreds of queries per second with millisecond latency while establishing engineering excellence and reliability for enterprise customers.
Key Responsibilities:
- Architect and optimize infrastructure handling billions of documents and hundreds of queries per second
- Drive migration from legacy systems to modern architecture with zero downtime and improved performance
- Establish comprehensive monitoring, testing, and deployment practices to catch issues before customers encounter them
- Profile and tune systems from infrastructure to application level, balancing cost and performance
- Lead platform evolution and own a critical system that directly impacts how customers discover insights
- Build observable systems with comprehensive monitoring and alerting
The role is perfect for a seasoned engineer with a track record of building robust, high-performance systems. While search experience is valuable, the company believes great engineers can master new domains—what matters most is the ability to build systems that scale reliably.
Within the first year, you'll transform search infrastructure from reactive to proactive, reduce latency, complete a major platform migration, and establish engineering practices that ensure reliability at scale.
AlphaSense is a market intelligence platform trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011 and headquartered in New York City, the company has 2,000+ employees across offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland.
REQUIREMENTS:
Required:
- 5+ years building and operating distributed systems in production
- Experience with large-scale data platforms or high-throughput systems
- Expertise in distributed systems fundamentals: sharding, replication, consistency, partition tolerance
- Strong performance optimization skills—ability to profile, diagnose, and fix bottlenecks across the stack
- Experience with data pipeline architecture, real-time processing, or database internals
- Excellence in building observable systems with comprehensive monitoring and alerting
Preferred:
- Experience with search platforms (Vespa, Elasticsearch, Solr) or similar large-scale data systems
- Experience with Kubernetes, CRDs, and infrastructure as code
- Background in information retrieval, ranking systems, or recommendation engines
- Familiarity with hybrid search approaches (lexical and vector)
- Experience with JVM-based systems and tuning
- Knowledge of modern engineering practices from high-growth companies
