Senior Product Manager, AI
Fully remote-friendly work environment within IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5–10 years
- Required Skills
- AgileCybersecurityProduct Management
Requirements
- 5–10 years of product management experience delivering complex technical software products and AI-driven solutions.
- Strong understanding of Agentic AI systems, LLMs, MCP frameworks, data pipelines, and large-scale platform architectures.
- Experience working with enterprise security domains such as SIEM, incident response, log management, or related areas.
- Strong UI/UX understanding with the ability to design user-centric workflows for technical platforms.
- Proven ability to translate complex technical concepts into clear product strategy and business value.
- Strong collaboration skills with engineering, design, data science, and business stakeholders in fast-paced environments.
- Experience managing full product lifecycles from ideation to delivery in Agile environments.
- Strong communication and stakeholder management skills with the ability to align cross-functional teams.
- Ability to operate effectively in ambiguous, evolving technology spaces such as AI and cybersecurity.
- Advanced degree in a technical field or MBA is preferred.
Responsibilities
- Define and drive the end-to-end product strategy and roadmap for AI platform services and agentic security workflows.
- Own product vision and execution for AI-driven capabilities, ensuring alignment between technical architecture and user experience.
- Collaborate closely with engineering, data science, and threat research teams to design scalable Agentic AI systems and autonomous workflows.
- Develop and maintain API frameworks and data ingestion capabilities to support high-performance, enterprise-grade integrations.
- Translate complex AI and security outputs into intuitive UI/UX workflows in partnership with design and front-end teams.
- Gather and incorporate feedback from enterprise customers, sales, and support teams to continuously improve product direction.
- Write detailed PRDs, user stories, and workflow specifications to guide engineering execution and sprint delivery.
- Prioritize and manage product backlogs by balancing technical feasibility, business value, and time-to-market considerations.
- Define architectural and deployment requirements across SaaS, hybrid, and on-prem environments, ensuring security and compliance.
- Lead go-to-market and enablement efforts in collaboration with product marketing and cross-functional stakeholders.
- Own the lifecycle and productization of MCP server architecture and cross-system AI agent interoperability frameworks.
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