AI Solutions Engineer – UAE

Location

United Arab Emirates — Offshore / On-site

Job Category

• Information Technology (IT) & Software
• Science & Research
• Engineering & Technical
• Banking & Insurance
• Business Development

Job Overview

Nair Systems is seeking an experienced AI Solutions Engineer to support its UAE operations across offshore and on-site engagements. The role is focused on designing, developing, deploying, and governing enterprise artificial intelligence solutions, with particular emphasis on machine learning, solution architecture, cloud technologies, Agentic AI, data integration, and digital transformation.

The successful candidate will work with AI and cloud platforms such as Microsoft Azure while integrating AI solutions with enterprise platforms including Salesforce CRM, data lakes, CMS platforms, and APIs. The role requires strong technical expertise across machine learning, deep learning, data processing, systems integration, containerization, DevOps, data architecture, security, and privacy.

The position offers strong career growth through exposure to advanced AI technologies and highly regulated financial services environments. Professional development in AI architecture, Agentic AI, Azure, machine learning, cloud engineering, and relevant AI certifications can further support long-term career progression.

Key Responsibilities

• Design, develop, and deploy scalable enterprise AI solutions.
• Lead AI solution architecture and ensure alignment with enterprise technology standards.
• Drive architecture governance, code quality, and technical standards.
• Develop and implement machine learning and deep learning solutions.
• Design and deploy Agentic AI solutions, autonomous AI agents, and multi-agent systems.
• Develop AI-powered workflow automation using platforms such as Azure AI Foundry and Agentforce.
• Work with AI frameworks and platforms including Hugging Face, LangChain, Foundry, and OpenAI APIs.
• Integrate AI solutions with Salesforce CRM, data lakes, CMS platforms, APIs, and legacy enterprise systems.
• Develop AI solutions using RESTful APIs and middleware integrations.
• Work with cloud infrastructure, Docker, Kubernetes, and DevOps practices.
• Design and support data pipelines, ETL processes, and data lakehouse environments.
• Work with data engineering platforms and lakehouse technologies such as Microsoft Fabric.
• Apply appropriate security, privacy, governance, and compliance controls to AI systems.
• Support AI and digital transformation initiatives within regulated environments.
• Collaborate with technical and non-technical stakeholders to define requirements and communicate complex AI concepts.
• Identify opportunities to improve AI architecture, scalability, performance, and operational efficiency.
• Support testing, deployment, monitoring, and continuous improvement of AI solutions.
• Contribute to AI governance, risk management, and regulatory compliance initiatives.

Requirements & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related discipline.
• 6–8 years of professional experience in AI, machine learning, solution architecture, or related fields.
• Proven experience designing and deploying enterprise AI solutions.
• Hands-on experience with AI tools, platforms, and cloud services such as Microsoft Azure.
• Strong knowledge of machine learning algorithms, deep learning, data processing, and systems integration.
• Experience driving architecture governance, code quality, and technical standards.
• Proven experience delivering AI and digital transformation solutions within financial services, banking, fintech, regulatory authorities, or highly regulated environments.
• Strong understanding of compliance, governance, risk management, and regulatory requirements.
• Proficiency in programming languages such as Python, Java, or C++.
• Familiarity with data pipeline tools and frameworks.
• Experience with cloud infrastructure, Docker, Kubernetes, and DevOps practices.
• Strong understanding of data architecture, data science, AI security, and privacy considerations.
• Experience integrating AI with enterprise platforms and legacy systems.
• Experience with Hugging Face, LangChain, Foundry, OpenAI APIs, or equivalent AI frameworks is advantageous.
• Demonstrated experience designing and deploying Agentic AI solutions, autonomous agents, multi-agent systems, AI orchestration frameworks, and agent-based workflow automation.
• Experience with platforms such as Azure AI Foundry and Agentforce is advantageous.
• Familiarity with data engineering tools, Microsoft Fabric, data lakehouses, and ETL pipelines.
• Strong understanding of RESTful APIs and middleware integration.
• Strong analytical and problem-solving skills.
• Excellent communication skills with both technical and non-technical stakeholders.
• Leadership experience and ability to work effectively within cross-functional teams.
• Strong attention to detail and commitment to delivering scalable, high-quality solutions.

Preferred Qualifications

• Experience with advanced AI techniques such as reinforcement learning, natural language processing, or computer vision.
• Knowledge of AI ethics and bias mitigation strategies.
• Relevant AI, cloud, machine learning, or architecture certifications.

Salary, Benefits & Career Growth

Salary details were not provided for this vacancy.

Specific employee benefits were not provided.

The position offers exposure to advanced AI engineering and solution architecture within financial services, banking, fintech, and other highly regulated environments. The role provides opportunities to work with Agentic AI, cloud platforms, enterprise integration, data lakehouses, machine learning, and digital transformation technologies.

Career progression can be supported through advanced AI architecture training, Microsoft Azure certifications, machine learning programs, Agentic AI specialization, cloud engineering education, and enterprise architecture development. Relevant professional certifications and continuous technical upskilling can support progression into AI Architect, Lead AI Engineer, AI Solutions Architect, Enterprise AI Architect, and AI Technology leadership roles.

Application Process

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