Senior Product Manager

Aqua Security is a global leader in cloud-native security, helping organizations secure modern applications across containers, Kubernetes, serverless, and AI-driven environments. As AI transforms how organizations build, operate, and secure software, Aqua is investing in the next generation of intelligent security products, including AI-powered experiences, assistants, and autonomous and semi-autonomous agents. We are looking for a Senior Product Manager to lead the strategy and execution of Aqua’s AI products and agents. This person will identify valuable customer problems, develop and validate new product concepts, and work closely with Engineering to turn them into high-quality products that customers can trust. This is a strategic and hands-on role for a product leader who combines strong business judgment, technical depth, product craft, and practical experience building AI or machine learning products. You will own the product direction and end-to-end experience, from market research, customer discovery, and early concepts through prototypes, production delivery, adoption, and continuous improvement. You will work directly with developers and designers throughout implementation, helping answer detailed questions about product behavior, workflows, UI, UX, and quality expectations. The successful candidate will connect customer and business needs with day-to-day product development, establish a clear quality bar, and help the team deliver a coherent, useful, and trusted product. What You Will Own • Define and drive the vision, strategy, and roadmap for Aqua’s AI products, agents, and related platform capabilities. • Identify high-value use cases for AI-assisted and autonomous workflows across cloud security, operations, and developer experiences. • Identify target users, buyers, decision-makers, and business value through customer discovery, market research, and competitive analysis. • Lead new product concepts and proofs of concept, using them to validate customer value, usability, technical feasibility, and commercial potential before broader investment. • Work directly with customers, partners, field teams, and internal stakeholders to understand pain points, validate assumptions, and uncover new opportunities. • Translate customer needs, market insights, and business objectives into clear product requirements, workflows, and differentiated capabilities. • Work closely with developers and designers throughout the development process, providing timely decisions on product behavior, edge cases, UI, UX, and expected outcomes. • Own the end-to-end product experience and acceptance bar, ensuring that the product is coherent, intuitive, reliable, and aligned with customer expectations. • Define how AI product quality will be evaluated, including answer quality, accuracy, safety, consistency, evidence, user trust, and appropriate handling of uncertainty. • Partner closely with Engineering, Security Research, Data Science, and Design to deliver scalable, production-ready AI solutions. • Drive both inbound and outbound product management, including customer discovery, market analysis, competitive intelligence, product positioning, and field engagement. • Define success metrics and use product analytics, customer feedback, and quality evaluations to improve adoption, engagement, and business impact. • Collaborate with Product Marketing, Sales, and Customer Success on messaging, enablement, launch planning, and go-to-market strategy. • Prioritize investments and make informed trade-offs across customer value, user experience, technical complexity, product quality, and business impact. • Represent the product internally and externally, acting as a trusted advisor to customers, partners, executives, and industry stakeholders.

Requirements: • 7+ years of Product Management experience, with a proven track record of launching and scaling enterprise software products. • Demonstrated experience working closely with engineering teams throughout product development, including resolving detailed questions about workflows, product behavior, edge cases, UI, and UX. • Proven ownership of end-to-end product quality and customer experience, with experience establishing clear acceptance criteria and helping teams meet a high product bar. • Strong experience in product discovery, UX, workflow design, and translating complex technical capabilities into simple and effective user experiences. • Experience leading new product concepts, prototypes, or proofs of concept in emerging or uncertain markets and developing them into validated product investments. • Experience building or managing AI, machine learning, analytics, automation, or other data-driven products. • Strong business orientation, including experience with product strategy, buyer and market analysis, go-to-market initiatives, and commercial outcomes. • Experience leading both inbound and outbound product management activities. • Strong technical foundation and the ability to engage in detailed discussions about cloud architecture, APIs, data pipelines, AI systems, and product trade-offs. • Proven experience working directly with enterprise customers and translating customer feedback into successful products. • Excellent communication, storytelling, and executive presentation skills. • Data-driven mindset, with the ability to define KPIs, product quality metrics, and measurable success criteria. • Strong collaboration and stakeholder management skills across technical and business teams. • High ownership and the ability to operate effectively in a fast-moving and evolving product environment. Nice to Have • Experience building AI assistants, copilots, agents, or workflow automation products. • Familiarity with LLMs, model capabilities and limitations, agent orchestration, retrieval techniques, prompt design, and AI evaluation methodologies. • Experience defining quality and trust standards for AI products, including accuracy, grounding, explainability, safety, and refusal behavior. • Background in cloud security, DevSecOps, cybersecurity, or cloud-native technologies. • Experience with Kubernetes, containers, and enterprise SaaS platforms. • Experience taking an AI or machine learning product from early concept through production adoption. • MBA or equivalent business experience