Senior Full Stack Engineer

Role Overview

Senior Full Stack Engineer at Deeplight, a specialist AI and data consultancy based in the UAE. This role bridges advanced data science and enterprise-scale software architecture, designed for engineers who combine deep mathematical and modeling expertise with full-stack infrastructure capabilities to deploy, containerize, scale, and monitor AI systems across hybrid, cloud, and on-premise environments.

Company Overview

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, the firm partners with organizations across diverse sectors, with deep-rooted expertise in Financial Services and Banking. Deeplight delivers tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, from building robust data foundations to deploying sophisticated AI platforms.

Role Purpose

You will own the full engineering lifecycle of AI applications, operating within complex client landscapes such as premier banking and financial institutions. You will design secure, highly performant systems, orchestrate massive data pipelines, optimize cloud spend, and establish robust MLOps practices that guarantee production stability. Your role combines technical mastery with the ability to bridge complex data science and actionable business value, serving as a compelling communicator and persuasive advocate for technical decisions to high-level stakeholders.

Key Responsibilities

Architecture & 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 (for example, 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.

Stakeholder Engagement

• Bridge the gap between complex data science and actionable business value through clear communication and persuasive advocacy.
• Articulate the "why" behind technical decisions and effectively sell your vision to high-level stakeholders.
• Build trust and serve as the face of the firm with clients.

Qualifications & Experience

• 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-tier software engineering skills in Python and advanced data processing techniques.

Preferred Qualifications

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a highly relevant quantitative discipline.
• Deep domain experience within banking, understanding strict data residency laws, financial compliance protocols, and legacy core banking interactions.
• Practical experience with agentic frameworks (for example, LangChain, LlamaIndex, AutoGen) and modern cloud MLOps suites (for example, Azure AI Studio, Kubeflow).

Additional Information

• Competitive salary
• Comprehensive personal health insurance
• Visa sponsorship for the successful candidate
• Professional development and certification support
• Subscription reimbursement relating to your role
• Opportunity to work on cutting-edge AI projects
• Monthly Employee Incentive program
• Career advancement opportunities in a rapidly growing AI company
• Deeplight AI is committed to fostering an inclusive environment where individuals with different thinking styles can thrive. Reasonable adjustments are available for the application and interview process.