Lead technical engagement with clients - Represent the company as the primary technical point of contact throughout discovery calls, site assessments, and solution walkthroughs, building the credibility that moves deals forward.
Translate technical capability into commercial value - Articulate how drone dock, quadruped/humanoid robotics, and RaaS solutions address specific client operational challenges, enabling the sales team to sell with confidence and precision.
Own end-to-end solution design - Assess client requirements and architect the corresponding hardware, software, and connectivity solution, working closely with engineering to validate technical feasibility before commitment.
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ParcelDaily is seeking a Quality Assurance (QA) Intern to work closely with developers, product, customer service, and operations to test and improve the ParcelDaily platform. The role involves testing workflows, courier integrations, parcel bookings, payment transactions, tracking updates, and other features used by customers.
Lead end-to-end project delivery, from technical discovery and solution scoping through on-premise deployment and final handover.
Work hands-on with CCTV / video surveillance environments — IP cameras, NVRs, video management systems (VMS), and live video feeds — to plan and execute AI Vision deployments across client sites.
Plan and oversee on-premise server and software deployment: hardware sizing, Linux environments, containers (Docker), networking, and security considerations, in partnership with our engineers.
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Build and lead the project delivery function: hire, mentor, and manage project managers; set delivery standards, playbooks, and KPIs.
Own portfolio-level delivery — timelines, budgets, quality — across all concurrent AI Vision, system integration, and enterprise deployment projects.
Personally lead the largest, most complex programs: CCTV / video surveillance rollouts, multi-site on-premise server and software deployments, and agentic AI initiatives (multi-agent orchestration systems, natural-language query layers over real-time vision event data, LLM tool-use and automation).
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