Senior Full Stack AI Engineer - AI Architecture & MLOps

deeplight ai United Arab Emirates
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AI Summary

Design, deploy, and manage advanced AI systems. Bridge data science and enterprise-scale software. Optimize cloud spend and MLOps. Collaborate with high-level stakeholders.

Key Highlights
End-to-End AI Architecture & Full-Stack Design
Deep Learning & Advanced AI Engineering
Infrastructure, MLOps & FinOps
Key Responsibilities
Architect end-to-end AI systems across on-premise and cloud
Design, build, and optimize high-throughput APIs
Implement deep learning models in NLP and CV domains
Build and automate MLOps CI/CD pipelines
Optimize cloud spend and inferencing costs
Technical Skills Required
Python AI/ML Cloud (Azure/AWS)
Benefits & Perks
Competitive salary
Comprehensive personal health insurance
Visa Sponsorship
Professional development and certification support
Nice to Have
Practical experience with agentic frameworks
Experience with modern cloud MLOps suites

Job Description


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.

Requirements

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

It would also be great if you have:

  • An 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 (e.g., LangChain, LlamaIndex, AutoGen) and modern cloud MLOps suites (e.g., Azure AI Studio, Kubeflow)

Benefits

The benefits you'll enjoy as part of this role include:

  • Competitive salary
  • Comprehensive personal health insurance
  • Visa Sponsorship for the successful individual
  • 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

This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.

At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.

Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.

If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

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