Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Shape and lead the development of a next-generation AI product ecosystem for business operations, owning the architecture and technical direction of production-grade agentic systems.
Compensation
Competitive annual salary: $200,000–$300,000, depending on experience, skills, and qualifications.
Responsibilities
Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
Staff AI Product EngineerNewJobgether · Remote, United Arab Emirates