AI Technical Lead

Other Positions

Dubai

June 30, 2026

Application ends: September 28, 2026

Job Description

REQUIREMENTS

Master’s degree in AI, Data Science, Computer Science, Business Analytics, or Technology Management is preferred.
Certifications in AI, cloud platforms, data science, enterprise architecture, project management, or agile delivery are an advantage.
Strong knowledge of AI, machine learning, deep learning, Generative AI, NLP, LLMs, analytics, and automation.
Hands-on experience with platforms and models such as OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, or similar.
Experience with Agentic AI, RAG, vector databases, embeddings, semantic search, AI copilots, chatbots, and workflow automation.
Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, LangGraph, or equivalent tools.
Strong programming and engineering experience, preferably in Python and modern API/microservices-based architectures.
Knowledge of cloud platforms such as Azure, AWS, or Google Cloud.
Understanding of MLOps, LLMOps, CI/CD, monitoring, evaluation, model governance, and production deployment.
Strong awareness of data privacy, cybersecurity, prompt injection risks, data leakage prevention, and responsible AI practices.
Excellent leadership, communication, stakeholder management, problem-solving, and strategic planning skills.
Experience in product-based software companies, SaaS, fintech, banking technology, capital markets technology, enterprise software, or regulated industries is preferred.
Experience integrating AI into enterprise products, internal workflows, or customer-facing platforms is highly desirable.
Capable of turning AI from a concept into secure, scalable, practical, and tangible solutions.

RESPONSIBILITIES

Identify AI opportunities across products, software development, QA, DevOps, support, sales, finance, HR, and operations.
Establish responsible AI practices covering security, privacy, compliance, explainability, auditability, and human oversight.
Present AI adoption progress, effectiveness and risks to executive leadership.
Lead AI research, experimentation, prototyping, proof-of-concepts, and MVP development.
Evaluate emerging AI technologies, LLMs, frameworks, tools, platforms, and cloud AI services.
Build reusable AI components, prompt libraries, knowledge bases, automation templates, and internal accelerators.
Convert R&D outcomes into production-ready product features, internal tools, or strategic business capabilities.
Act as the company’s AI champion and drive AI adoption across all departments.
Conduct awareness sessions, training programs, workshops, and use-case discovery sessions.
Help teams use AI to improve productivity, documentation, development, testing, support, analysis, and decision-making.
Create internal AI usage guidelines, prompt engineering guides, best practices, and safe-use policies.
Track adoption, productivity gains, quality improvements, and process efficiencies.
Lead the design and implementation of AI-powered features within the company’s products.
Build and deploy Agentic workflows, copilots, chatbots, intelligent assistants, smart search, document intelligence, analytics, and automation features.
Work with product, architecture, development, QA, DevOps, and business teams to deliver secure, scalable, and reliable AI solutions.
Design AI solution architectures using LLMs, RAG pipelines, vector databases, APIs, orchestration frameworks, cloud services, and monitoring tools.
Support AI-related product demos, client presentations, proposals, and solution positioning.