AI Forward Deployed Engineer
Network International · United Arab Emirates
Job Description
Job Role
AI Forward Deployed EngineerGrade
Senior ManagerReporting to
AI Project Portfolio Lead
Location
Dubai, United Arab Emirates
Job Purpose
About Network International: Network International is the largest financial technology company in the Middle East and Africa. Payments is our core business, and we provide services across more than 50 countries, including key markets such as the UAE, Jordan, South Africa and Egypt. In addition to payments, we offer solutions across data and insights, lending, insurance and risk management. Our customers include businesses of every scale and segment, with growing direct-to-consumer card offerings.
Our Employee Value Proposition: At Network International, we always stay ahead. In the fast-paced world of financial services, we thrive on innovation, agility and purposeful collaboration. We invest first in our people, empowering them to make bold decisions, learn fast and develop their expertise alongside industry leaders. Here, solving complex problems means more than using cutting-edge technology; it is about creating meaningful value for our customers together. We foster a culture where trust, accountability and achievement go hand in hand, because success is not just a goal; it is how we work every day, as one team.
About the Role: The AI Forward Deployed Engineer embeds directly into priority enterprise AI projects — with a particular focus on AI Champion–led initiatives — to turn approved solution designs into working, production-ready applications, agents, automations and integration flows. The role provides hands-on engineering leadership across the full build lifecycle, from technical design and architecture decisions through prototyping, testing, deployment and production handover, making sure solutions are secure, scalable and reusable rather than one-off demos.
Working under the direction of the AI Project Portfolio Lead, the role collaborates with AI Champions, Data Scientists, Technology, Architecture, Data and Information Security teams to deliver enterprise-grade AI solutions at pace. While solution scoping and prioritisation sit with the AI Portfolio & Solutioning Lead, this role validates and enhances designs at the point of implementation, feeding practical build learnings back into solutioning, the AI Factory and shared engineering standards. It also enables AI Champions to build solutions independently by making the right architecture choices, providing reusable components and offering practical, hands-on technical support across development, testing and deployment.
Key Accountabilities
- Embed into selected AI Champion and business-unit projects to implement approved solution designs as working technical components, applications, agents, automations and integration flows.
- Make and enforce sound technical, integration and architecture decisions so solutions are secure, scalable, maintainable and reusable across the organisation.
- Validate, pressure-test and enhance solution designs at implementation, feeding practical build learnings back to the AI Portfolio & Solutioning Lead.
- Design, prototype, build, configure and test AI applications, copilots, agents, automations and orchestration workflows using approved enterprise platforms and technologies.
- Develop solution prototypes and production-ready components using advanced prompting, front-end and back-end coding, low-code tools, APIs and cloud-based AI services.
- Coach AI Champions hands-on in designing and building data pipelines, agentic workflows, automations and software applications while reinforcing approved technical and delivery standards, keeping them in the driver's seat.
- Stay ahead on emerging AI technologies, tools and frameworks for building applications and agentic workflows, and schedule internal sessions to teach and upskill AI Champions.
- Build and maintain reusable prompt templates, skills, tools, workflows, code components and reference implementations for organisation-wide use.
- Integrate AI solutions with approved enterprise data sources, APIs, applications, identity services, hosting environments and AI Factory capabilities.
- Implement retrieval-augmented generation, tool use, workflow orchestration and other appropriate AI engineering patterns based on solution requirements.
- Apply working machine learning knowledge to operate AI tooling, run Python and evaluate model outputs; hands-on model building is appreciated but is not the core focus of the role.
- Prepare and execute functional testing, integration testing, user acceptance testing, model evaluation, red-teaming and guardrail testing for selected solutions.
- Support AI Champions and project teams in defining test scenarios, acceptance criteria, evaluation datasets and quality thresholds.
- Apply approved security, privacy, responsible AI and engineering controls throughout development, testing and deployment.
- Diagnose and resolve technical issues involving prompts, agents, APIs, integrations, authentication, data access, environments and platform configurations.
- Maintain clear technical documentation covering solution components, configurations, interfaces, deployment procedures, testing results and operational dependencies.
- Track technical requests, defects, integration needs and deployment dependencies, ensuring clear ownership and timely follow-through.
- Coordinate with Technology teams on code review, source control, release management, environment promotion, production deployment and operational handover.
- Monitor early production performance and support the resolution of technical issues following deployment.
- Identify opportunities to improve solution quality, engineering standards, developer experience, reuse and delivery speed across the AI transformation program.
- Provide clear technical updates, risks and recommendations to the AI Portfolio & Solutioning Lead and relevant project stakeholders.
- Contribute to a collaborative, accountable and performance-driven engineering culture focused on secure delivery and measurable business value.
Experience, Skills & Success Profile
Experience & Qualifications
- Extensive hands-on experience in software engineering, AI engineering, application development, automation or a related technical role, including experience operating as an embedded or forward-deployed engineer alongside delivery teams.
- Bachelor's degree in computer science, software engineering, information technology, data science or a related discipline, or equivalent professional experience.
- Demonstrated experience designing, developing, testing and deploying enterprise applications, integrations or AI-enabled solutions into production.
- Practical experience with generative AI, large language models, copilots, AI agents, prompt engineering, retrieval-augmented generation and workflow orchestration.
- Strong programming capability in Python, JavaScript, TypeScript, C# or another relevant enterprise development language.
- Working machine learning knowledge sufficient to operate AI tooling, run Python and evaluate models; practical model-building experience is appreciated but not essential.
- Experience working with APIs, software development kits, web services, authentication mechanisms, structured data and enterprise system integrations.
- Familiarity with cloud AI services, enterprise AI platforms, agent development frameworks, automation tools and low-code development environments.
- Experience with version control, code review, testing frameworks, continuous integration and deployment practices.
- Sound understanding of software architecture, application security, identity and access management, data privacy and secure development practices, with the judgment to make architecture decisions at implementation.
- Experience preparing technical designs, interface specifications, test plans, deployment documentation and operati