Integrate enterprise applications through authenticated APIs and MCP where appropriate, selecting deterministic workflows, agents or conventional ML based on the problem.
Product instinct developed through 2+ years of product thinking(formal PM title not required). Demonstrated ability to define metrics, design systematic data collection, and translate user signals into prioritised decisions.
Build Source Channels — Develop YouTube and LinkedIn as strategic channels for both organic discovery and AI-search visibility. Work with content and video freelancers to create, distribute, and optimise content that compounds over time.
You will work closely with robotics software, AI perception, navigation, mechatronics, and system engineering teams to translate advanced AI and simulation methods into reliable robot capabilities for real-world deployment.
Design and implement RAG pipelines and LLM application workflows (prompting, retrieval, tool calling, agents), and expose them as reliable, scalable services.
The engineer will support Active Directory Domain Services (AD DS), Group Policy Management, DNS, DHCP, Microsoft Entra ID (Azure AD), Microsoft 365 integration, VMware infrastructure, and Windows Server environments while ensuring compliance with operational standards, security policies, audit requirements, and service level commitments.
Drive the integration of AI capabilities with code repositories, CI/CD pipelines, testing platforms, deployment environments, and knowledge platforms to deliver a unified end-to-end product experience.