AI Agent Platform Product Manager

Remotedxb; Dubai; On-site; AED 300,000 - 600,000; Full time

Job summary

Remotedxb is seeking a Product Owner for its AI Agent platform to lead product planning, roadmaps, and delivery. The role focuses on identifying reusable platform capabilities from diverse business needs and designing end-to-end lifecycle management for Agents, including creation, configuration, debugging, deployment, and optimization.

The ideal candidate has 5+ years in product management, deep knowledge of AI Agents and enterprise SaaS, and proven ability to collaborate with algorithm and

Qualifications

• 5+ years of product management experience.
• Experience with AI Agents, AI mid-platforms, developer platforms, low-code platforms, or enterprise SaaS.
• Proven Product Owner capability in requirement judgment, planning, and project execution.
• Platform-oriented product thinking with the ability to abstract general capabilities from complex requirements.
• Understanding of LLM and AI Agent principles, including Prompt Engineering, Tool Calling, RAG, Workflow, Memory, and LLMOps.
• Strong technical understanding to communicate effectively with algorithm and engineering teams.
• Result-oriented mindset focused on platform usage, capability reuse, and ROI.

Responsibilities

• Act as the Product Owner responsible for the AI Agent platform's product planning, roadmap, and delivery.
• Identify common scenarios from diverse business needs to build standardized, reusable platform capabilities.
• Design the complete product lifecycle for Agents, including creation, configuration, debugging, evaluation, deployment, monitoring, and optimization.
• Drive core capabilities such as workflow orchestration, multi-agent collaboration, task decomposition, and intelligent routing.
• Build tool calling, API, plugin, and MCP tool integration systems.
• Advance enterprise knowledge bases, RAG, memory, context management, and model routing capabilities.
• Implement permission controls, data security, audit trails, exception retries, and human-in-the-loop mechanisms.
• Establish Agent evaluation and operational metric systems to optimize task completion rates, accuracy, stability, and cost.
• Coordinate with algorithm, engineering, data, and security teams to ensure high-quality delivery.
• Define Agent integration standards and best practices to lower the barrier for business teams.

Skills

Product Management

AI Agents

Enterprise SaaS

Product Owner

LLM & AI Agent principles

Technical communication

Job description

Responsibilities

• Act as the Product Owner responsible for the AI Agent platform's product planning, roadmap, and delivery.
• Identify common scenarios from diverse business needs to build standardized, reusable platform capabilities.
• Design the complete product lifecycle for Agents, including creation, configuration, debugging, evaluation, deployment, monitoring, and optimization.
• Drive core capabilities such as workflow orchestration, multi-agent collaboration, task decomposition, and intelligent routing.
• Build tool calling, API, plugin, and MCP tool integration systems.
• Advance enterprise knowledge bases, RAG, memory, context management, and model routing capabilities.
• Implement permission controls, data security, audit trails, exception retries, and human-in-the-loop mechanisms.
• Establish Agent evaluation and operational metric systems to optimize task completion rates, accuracy, stability, and cost.
• Coordinate with algorithm, engineering, data, and security teams to ensure high-quality delivery.
• Define Agent integration standards and best practices to lower the barrier for business teams.

Requirements

• 5+ years of product management experience.
• Experience with AI Agents, AI mid-platforms, developer platforms, low-code platforms, or enterprise SaaS.
• Proven Product Owner capability in requirement judgment, planning, and project execution.
• Platform-oriented product thinking with the ability to abstract general capabilities from complex requirements.
• Understanding of LLM and AI Agent principles, including Prompt Engineering, Tool Calling, RAG, Workflow, Memory, and LLMOps.
• Strong technical understanding to communicate effectively with algorithm and engineering teams.
• Result-oriented mindset focused on platform usage, capability reuse, and ROI.

Preferred Qualifications

• Familiarity with MCP, API gateways, plugin systems, and enterprise system integration.
• Experience in multi-agent collaboration, intelligent workflows, Agent evaluation, or model routing.
• Experience in complex business scenarios such as finance, trading platforms, risk control, or operational automation.