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Hazelcast is looking for an experienced Senior Product Manager to drive the strategy and delivery of enterprise-grade platform capabilities. In this role, you will own the roadmap for resilience, reliability, and performance features that our largest customers depend on—working at the intersection of distributed systems, Java-based infrastructure, and open-source community engagement. You will partner closely with engineering teams based primarily in Europe, requiring comfort with cross-timezone collaboration and occasional overlap with European working hours. This is a high-impact role for someone who thrives in technically deep product work and wants to shape the future of real-time data infrastructure.
Job Responsibility:
Own the product roadmap for enterprise platform capabilities, including resilience, fault tolerance, high availability, data consistency, and disaster recovery features
Work closely with core platform engineering teams building distributed data store and streaming analytics capabilities in a Java-based, open-source environment
Partner with engineering to define, scope, and deliver features that meet the demanding reliability and performance requirements of Fortune 500 customers
Collaborate with Engineering and QA teams to ensure performance, scalability, and resiliency targets are met for customer workloads at scale
Engage with the open-source community and ecosystem to inform product direction, gather feedback, and drive adoption of Hazelcast’s open-source offerings
Become a deep product expert in Hazelcast’s real-time data platform, including in-memory data grid, streaming, and caching capabilities
Collaborate cross-functionally with Documentation, Solution Architects, Sales Engineering, and Product Marketing to translate technical capabilities into customer value
Work effectively across time zones with Europe-based engineering teams, including regular overlap with CET/GMT working hours
Champion the adoption of AI-powered tooling and agentic workflows across product management and engineering processes—from AI-assisted product discovery and specification writing to leveraging coding agents and LLM-based tools to accelerate development velocity
Build strong trust with distributed teams and effectively negotiate backlog prioritization and release planning
Requirements:
5+ years of Product Management experience with enterprise software platforms
First-hand experience working with distributed systems, database internals, or middleware—you should be comfortable with topics like replication, consistency guarantees, shared-nothing architectures, threading models, and fault-tolerance patterns
Strong background working in Java-based technology environments
familiarity with the Java ecosystem, JVM performance characteristics, and enterprise Java frameworks
Demonstrated experience delivering resilience and reliability features for enterprise-grade products (e.g., high availability, disaster recovery, data replication, failover mechanisms)
Experience working with or contributing to open-source projects
understanding of open-source community dynamics, licensing, and go-to-market considerations
A computer science or related technical degree
advanced technical degree is a plus
Exceptional verbal and written communication skills with the ability to translate complex technical concepts for diverse audiences
Data-driven and analytical mindset with strong product discovery and validation skills
Hands-on experience using AI tools and agents to enhance product management and engineering workflows (e.g., LLM-based coding assistants, AI agents for research and analysis, automated testing and documentation tooling)
Proven track record of building trust and collaborating effectively with remote, globally distributed engineering teams
Nice to have:
Proficiency in one or more European languages (e.g., German, French, Turkish, Polish, or others) in addition to English
Experience working directly with European enterprise customers or across EU markets
Familiarity with cloud-native infrastructure (Kubernetes, containers, managed cloud services) and how enterprise platforms are deployed in hybrid or multi-cloud environments
Experience with real-time or event-driven architectures, stream processing, or in-memory computing technologies
Track record of driving AI/ML integration into product strategy or engineering operations at a previous organization
Background in pricing and packaging for enterprise platform products