Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement.
Create clear functional and technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria that guide high-quality delivery.
Design, develop, test, deploy, and maintain modern full-stack, cloud-native applications that are secure, scalable, resilient, observable, and maintainable.
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Perform engineering analysis to identify optimal solutions based on client drivers and be able to efficiently communicate these solutions through technical reports and presentations
Carry-out techno-economic analyses for energy projects (upstream, mid-stream, down-stream but also renewables)
Work on key Energy Transition topics such as Hydrogen, CCUS, Ammonia, Biofuels and biowaste, etc
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Partner with customers to understand business challenges, operational requirements, and strategic priorities, and identify opportunities where AI/ML, GenAI, and Advanced Analytics can create measurable value.
Facilitate customer discovery sessions, workshops, requirements gathering, and solution-definition exercises.
Evaluate business processes, data availability, technology environments, and organizational readiness to determine suitable AI/ML approaches.
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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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