Develop and maintain enterprise-grade APIs to support banking operations, digital channels, and external integrations.
Ensure all API solutions adhere to internal security policies, regulatory standards, and data privacy requirements.
Collaborate with business stakeholders, solution architects, and development teams to translate functional requirements into technical API specifications.
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Contribute toward AI roadmap for AI-driven automation aligning with strategic company and client goals.
Collaborate with engineering and data teams to design and architect scalable, robust, and innovative AI solutions (e.g., automated network diagnostics, bot recommendation systems, AI agents NOC operations).
Act as the Solution Owner in an Agile/Scrum environment, managing the product backlog, writing detailed user stories, defining acceptance criteria, and prioritizing features.
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Act as a primary technical counterpart and architecture partner - designing, coding, and deploying a suite of custom, intelligent AI tools, and critically reviewing design decisions.
Enhance our system's ability to manage context windows, optimize token usage, and reduce attention noise when connecting LLMs to large codebase repositories.
Design and extend graph based code and document representations (e.g. property graphs, AST derived structures) and hybrid retrieval pipelines (dense + sparse + reranking/fusion) over vector databases.
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Core Focus: Growth, innovation, and cross-regional execution.
Marketing Integration – Partner with Marketing to turn consumer/competitor insights into tailored product concepts, value propositions, and pricing/commercialization strategies for local markets.
Pipeline Activation – Identify and warm up high-potential accounts via pre-sales (technical consults, feasibility, ROI), building a qualified handover pipeline for the sales team.
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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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