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Lead Forward Deployed Engineer
Mada Media DXB
Dubai, UAE
Full-time
Mid-Senior
Onsite
Discovered 1 weeks ago
LLM application developmentPrompt engineeringRetrieval-augmented generationAgentic workflowsOCR and document intelligenceREST APIs and webhooks
Free
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LLM application developmentPrompt engineeringRetrieval-augmented generation
Role Overview
Design, build, and deploy AI-enabled applications and automation solutions for business and operational requirements.
The role combines AI, APIs, workflow automation, RPA, data engineering, custom development, and stakeholder collaboration.
Key Skills for This Role
LLM application developmentPrompt engineeringRetrieval-augmented generationAgentic workflowsOCR and document intelligenceREST APIs and webhooks
Full Job Posting
Role focus
Design, build, and deploy AI-enabled applications and automation solutions for business and operational requirements.
The role combines AI, APIs, workflow automation, RPA, data engineering, custom development, and stakeholder collaboration.
AI and document intelligence
- Use LLMs, prompt engineering, RAG, agentic workflows, and evaluation frameworks to develop AI-enabled applications.
- Develop document intelligence solutions using OCR and LLM-based extraction, classification, and validation for permits, contracts, compliance documents, and operational records.
Integrations and automation
- Connect permit databases, CRM, finance and ERP systems, e-signature platforms, payment gateways, government-facing systems, and other enterprise platforms using REST APIs and webhooks.
- Build workflows with n8n, Zapier, Make, Airflow, or custom Python services, including routing, approvals, notifications, and exception handling.
- Develop RPA solutions for legacy systems, external portals, and applications where API integration is unavailable or impractical.
Python, data, and applications
- Develop Python services, scripts, data-processing components, and LLM orchestration solutions.
- Design and maintain SQL databases, data models, and data pipelines for permit, contract, inspection, compliance, and operational data.
- Build lightweight internal applications, dashboards, and interfaces for workflow users, output review, exception management, and operational insights.
Engineering and cloud delivery
- Apply Git-based version control, testing, and CI/CD practices for repeatable development and deployment.
- Deploy and operate AI, automation, integration, and data solutions on AWS, Azure, or GCP.
- Apply monitoring, logging, configuration, and error-handling practices to deployed solutions.
Stakeholder delivery
- Develop reporting and visualization solutions that convert operational data into actionable information.
- Prototype and iterate with business users while prioritizing early validation and continuous improvement.
- Work with business and operational stakeholders to understand processes, identify automation opportunities, and support adoption.
Evaluation and solution design
- Evaluate solution performance, build test and evaluation datasets, identify failure modes, and improve accuracy, reliability, and scalability.
- Use technical judgment to select the appropriate combination of AI, APIs, workflow automation, RPA, data engineering, and custom development.
Role capabilities
- The description supports capability in AI application development, automation, integrations, data engineering, cloud deployment, and stakeholder-facing solution delivery.
- The description does not provide a separate education, experience, certification, or preferred-qualification section.
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