Senior Full Stack Engineer

About the role

DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. Based in the UAE, we partner with organizations across diverse sectors-with a deep-rooted expertise in Financial Services and Banking-to bridge the gap between complex data and actionable business strategy. At DeepLight, we don't believe in "off-the-shelf" fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world. As a Senior Full Stack AI Engineer, you will be the ultimate bridge between advanced data science and enterprise-scale software architecture. This role is designed for a rare breed of engineer: someone who possesses the deep mathematical and modeling background required to design advanced AI and Generative AI systems, paired with the full-stack infrastructure capabilities needed to deploy, containerize, scale, and monitor them across hybrid, cloud, and on-premise environments. Operating within complex client landscapes-such as premier banking and financial institutions (e.g., ADCB)-you will own the full engineering lifecycle of AI applications. You will design secure, highly performant systems, orchestrate massive data pipelines, optimize cloud spend, and establish robust MLOps practices that guarantee production stability. Key Responsibilities End-to-End AI Architecture & Full-Stack Design Architect end-to-end, highly secure AI and Generative AI systems capable of running seamlessly across both secure on-premise data centers and public cloud infrastructures (Azure/AWS). Design, build, and optimize high-throughput, secure APIs to serve complex AI models and agentic workflows to consuming client applications. Seamlessly integrate proprietary cloud foundation models (GPT, Claude, Gemini) and fine-tuned open-source models into unified software ecosystems. Deep Learning & Advanced AI Engineering Leverage a deep theoretical understanding of Transformers, PyTorch, and TensorFlow to implement, evaluate, and optimize deep learning models across NLP and Computer Vision domains. Design scalable knowledge retrieval frameworks using embedding models and enterprise-grade Vector Databases (e.g., Azure DocumentDB, Elasticsearch, Faiss). Build and evaluate robust systematic prompting frameworks and compile complex models using ONNX for optimized, low-latency production inference. Infrastructure, MLOps & FinOps Own the containerization and scaling of AI services utilizing Docker and Kubernetes clusters across development and production environments. Build and automate robust MLOps continuous integration and deployment pipelines to track model lineage, versions, evaluations, and production drift. Implement strict FinOps practices to track, monitor, and radically optimize token usage, cloud compute consumption, and inferencing costs. Architect and optimize large-scale data processing systems using modern Big Data tools to feed raw information into AI training and embedding workflows. As an AI consultancy, our greatest asset is the expertise of our people. While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight. We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills. You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders. If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in. We need you to have: Extensive experience designing, launching, and managing containerized AI/ML or data-intensive applications in highly regulated enterprise environments. A proven track record applying deep learning models across both Natural Language Processing (NLP) and Computer Vision (CV) fields. Practical experience implementing production-grade model monitoring frameworks and optimizing complex cloud/token expenditure. Deep operational command of Docker and enterprise Kubernetes infrastructure for running distributed AI applications. Expert-level knowledge of Azure (or alternative major clouds) alongside a strong architectural grasp of on-premise deployment constraints, data security, and network topologies. Strong proficiency in Big Data toolsets and modern API gateway designs. A rigorous, foundational grasp of transformer architectures, embedding mechanics, and deep learning implementations via PyTorch/TensorFlow. High proficiency across SQL, NoSQL, and Vector Database engines. "Perfect-

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