AI Engineer

Senior AI Agentic & Automation Engineer
Location: Abu Dhabi, United Arab Emirates (On-site)
Job Type: Full-Time
Role Overview
An experienced, hands-on Senior AI Agentic & Automation Engineer is required to lead the technical architecture and execution of an autonomous employee agents platform and executive systems. The role focuses on building and orchestrating complex autonomous multi-agent workflows and enterprise automations, including invoicing, procurement, visa processing, and real-time executive reporting.
The position is responsible for designing the orchestration layer for intelligent agents, ensuring secure system integrations, and implementing verification controls that improve reliability, reduce hallucinations, and support factual accuracy in production workflows.
Minimum Experience
Candidates must have not less than 5 years of professional experience in software engineering, backend engineering, AI applications, automation engineering, or related technical roles, with proven hands-on delivery of production-grade systems.
Key Responsibilities
Design, develop, and optimize autonomous multi-agent systems and reasoning loops using frameworks such as LangChain, LangGraph, and LlamaIndex.
Build scalable workflow automations using tools such as n8n and Microsoft Power Automate.
Architect, develop, and maintain robust backend services, APIs, microservices, background jobs, and integration layers to support agent orchestration and enterprise workflows.
Integrate internal databases, enterprise systems, Tally accounting software, communication channels, and third-party APIs.
Develop retrieval-augmented generation (RAG) pipelines, verification layers, and evaluation mechanisms to improve response accuracy and reduce hallucinations.
Handle AI/ML model training, tuning, evaluation, and deployment using Hugging Face and GPU-enabled environments.
Write production-ready backend and integration code using Python and Node.js.
Design secure and scalable data architectures using platforms such as Supabase and MongoDB.
Implement logging, monitoring, auditability, validation rules, and approval workflows for high-risk automated actions.
Rapidly prototype, test, and ship features using tools such as Claude Code, OpenAI Codex, Lovable, Replit, or similar platforms.
Collaborate with business and executive stakeholders to translate operational requirements into autonomous, measurable workflows.
Required Qualifications
Minimum 5 years of professional experience in AI engineering, Full stack engineering, automation engineering, software engineering, or related fields.
Proven experience building and deploying production-grade AI applications, backend systems, agentic systems, or workflow automations.
Strong hands-on experience in designing AI workflow orchestration, reducing model hallucinations, and building scalable Agentic AI architectures.
Strong programming skills in Python and Node.js.
Solid hands-on backend development experience in building REST APIs, web services, system integrations, authentication flows, and scalable server-side applications.
Practical experience with LangChain, LangGraph, LlamaIndex, or comparable agentic frameworks.
Strong experience with automation tools such as n8n.
Experience with database platforms such as Supabase, and relational systems.
Hands-on experience with APIs, integrations, authentication, and secure system design.
Practical knowledge of model evaluation, accuracy measurement, prompt control, and output verification.
Familiarity with Hugging Face, GPU resources, and model training or fine-tuning workflows.
Strong problem-solving, architecture, and documentation skills.
Preferred Qualifications
Experience in procurement, HR, visa, finance, or executive reporting automation.
Experience integrating with ERP or accounting systems.
Familiarity with multi-tenant enterprise system design.
Experience with rapid development platforms and AI coding assistants.
Ability to work effectively in a fast-paced, on-site business environment in Abu Dhabi.
Strong plus: experience with GPU-based AI workloads, NVIDIA DGX environments, DevOps awareness , model serving, MLOps, vector databases, and high-performance AI infrastructure.