This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
AlphaSense is seeking an experienced engineering leader to own and scale our search platform that powers market intelligence across billions of documents. You'll tackle the challenge of building distributed systems that handle hundreds of queries per second with millisecond latency, while establishing engineering excellence that ensures reliability for our enterprise customers.
Job Responsibility:
Scale Distributed Systems: Architect and optimize infrastructure handling billions of documents and hundreds of queries per second
Lead Platform Evolution: Drive the migration from legacy systems to modern architecture, ensuring zero downtime and improved performance
Build Engineering Excellence: Establish comprehensive monitoring, testing, and deployment practices that catch issues before customers do
Optimize Performance: Profile and tune systems from the infrastructure to the application level, balancing cost and performance
Drive Technical Strategy: Own the platform roadmap, making architectural decisions that will scale 10x
Mentor and Lead: Elevate the team's expertise in distributed systems and large-scale data challenges
Requirements:
8+ years building and operating distributed systems in production
Experience with large-scale data platforms (billions of records) or high-throughput systems (100+ QPS)
Track record of improving system reliability and performance at scale
Deep expertise in distributed systems fundamentals: sharding, replication, consistency, partition tolerance
Strong performance optimization skills - you can 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
History of leading technical initiatives and mentoring engineering teams
Nice to have:
Experience with search platforms (Vespa, Elasticsearch, Solr) or similar large-scale data systems
Deep knowledge of 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