AI Solutions Engineer

Dautom; Dubai; On-site; AED 180,000 - 320,000; Full time

Benefits offered by this job

Competitive compensation

Professional development

Job summary

Dautom is seeking an AI Solutions Engineer to design, develop, and deploy AI-driven solutions across BFSI, Retail, Industrial, and Manufacturing. The role emphasizes translating business requirements into scalable AI architectures and production-ready applications.

You will work with data engineers and software teams to integrate AI capabilities into enterprise platforms, ensuring performance and reliability across cloud and on-prem environments. Proficient Python and ML frameworks are required.

Qualifications

• Bachelor's or master's degree in CS/Engineering/Data Science/AI or related field.
• 3+ years of AI/ML solution development with production-grade implementations.
• Experience in at least two domains: BFSI, Retail, Industrial, or Manufacturing.
• Strong Python programming and ML framework experience (TensorFlow, PyTorch, scikit-learn).
• Experience with structured and unstructured data (time-series, text, image).
• Cloud and on-prem deployment across AWS, Azure, or GCP; data pipelines and scalable architectures.

Responsibilities

• Engage with stakeholders across BFSI, Retail, Industrial, and Manufacturing to understand processes and AI adoption opportunities.
• Translate requirements into AI/ML architectures, designs, and proposals.
• Design, develop, and deploy end-to-end AI solutions including data prep, model development, testing, deployment, and monitoring.
• Build POCs, prototypes, and production-ready apps tailored to industry needs (BFSI, Retail, Industrial, Manufacturing).
• Collaborate with data engineers and software teams to integrate AI into enterprise platforms and applications.
• Evaluate model performance and improve accuracy, scalability, and reliability.

Skills

Python programming

Analytical thinking

Effective communication

Education

Bachelor's or master's in CS/Engineering/Data Science/AI

Tools

TensorFlow

PyTorch

scikit-learn

Docker

Kubernetes

Job description

About the Role

We are seeking a highly motivated and experienced AI Solutions Engineer to design, develop, and deploy AI-driven solutions that address complex business challenges across multiple industries. The successful candidate will play a pivotal role in translating business requirements into scalable, intelligent, and production-ready AI solutions, ensuring alignment between technical implementation and strategic business objectives.

The role requires hands-on expertise in Artificial Intelligence (AI), Machine Learning (ML), and end-to-end solution development, with practical domain knowledge across Banking, Financial Services and Insurance (BFSI), Retail, Industrial, and Manufacturing sectors.

The ideal candidate will have the ability to identify high-impact AI use cases and deliver innovative solutions for challenges such as fraud detection, demand forecasting, predictive maintenance, intelligent automation, and process optimization.

Key Responsibilities

• Engage with business stakeholders across BFSI, Retail, Industrial, and Manufacturing sectors to understand business processes, operational challenges, and opportunities for AI adoption.
• Translate business requirements into technical solution designs, AI/ML architectures, implementation strategies, and proposals.
• Design, develop, and deploy end-to-end AI solutions, encompassing data collection, preprocessing, model development, testing, deployment, and ongoing monitoring.
• Build proof of concepts (POCs), prototypes, and production-ready applications tailored to industry-specific requirements, including:
• BFSI: Credit scoring, fraud detection, customer segmentation, and risk modelling.
• Retail: Personalisation, demand forecasting, inventory optimisation, and customer analytics.
• Industrial and Manufacturing: Predictive maintenance, automated quality inspection, and process optimisation.
• Collaborate with data engineers, software developers, and cross‑functional teams to integrate AI capabilities into enterprise platforms and business applications.
• Evaluate model performance, troubleshoot issues, and continuously enhance the accuracy, scalability, reliability, and efficiency of deployed solutions.
• Ensure AI solutions align with business objectives, technical standards, data requirements, and operational expectations.
• Keep abreast of emerging AI/ML technologies, industry developments, and best practices to identify opportunities for innovation and continuous improvement.

Required Qualifications and Experience

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related discipline.
• Minimum of 3 years of relevant experience in AI/ML solution development, including hands‑on experience delivering production‑grade implementations.
• Practical experience in at least two of the following industry domains: BFSI, Retail, Industrial, or Manufacturing.
• Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit‑learn.
• Experience working with structured and unstructured data, including time‑series, text, and image datasets.
• Proficiency in designing scalable AI architectures, data pipelines, and deployment solutions across cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform, as well as on‑premises environments.
• Strong analytical and problem‑solving skills, with the ability to translate complex business challenges into effective technical solutions.
• Excellent communication and stakeholder‑management skills, with the ability to explain technical concepts to both technical and non‑technical audiences.

Preferred Qualifications

• Experience developing domain‑specific AI applications, such as OCR‑based invoice processing, customer churn prediction, or industrial robotics.
• Familiarity with containerisation and orchestration technologies, including Docker and Kubernetes.
• Knowledge of MLOps practices covering model deployment, versioning, monitoring, and lifecycle management.
• Exposure to big data technologies such as Apache Spark, Hive, or Kafka.
• Experience working in Agile/Scrum environments and collaborating with multidisciplinary teams.
• Demonstrated ability to manage AI initiatives from initial concept through development, deployment, and continuous improvement.

What We Offer

• A competitive compensation and benefits package.
• Opportunities to work on innovative AI initiatives across diverse industry verticals.
• A collaborative and innovation‑driven work environment.
• Opportunities for professional development, continuous learning, and exposure to emerging technologies.
• The opportunity to contribute to impactful AI solutions that drive business transformation and operational excellence.