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.

• 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.

• 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