AI Engineer

GIG Gulf is part of the Gulf Insurance Group (GIG), the #1 largest regional composite insurer in the Middle East and North Africa, with presence in 13 markets including the United Arab Emirates, Bahrain, Oman, Qatar, Saudi Arabia, Algeria, Egypt, Iraq, Jordan, Kuwait, Lebanon, and Turkey. GIG Group reported consolidated assets of US$ 3.83 billion and $69 million net profit for the year 2023. The majority shareholder of GIG Group is Toronto based Fairfax Financia Holding, a global leader in insurance and reinsurance with a presence in 40 markets.

GIG Gulf is an ‘A’ rated regional insurer with a top 5 position in each of its markets (UAE, Oman, Qatar, Bahrain). GIG Gulf has been present in the region for over 70 years with a strategic focus on both growth and investments and is a one stop shop offering a wide range of insurance products and services that cater to a broad variety of needs for corporates, SMEs and individual customers throughout UAE, Oman, Bahrain, and Qatar. GIG Gulf also owns a 50% stake in GIG Saudi. Our strategic objectives and guiding principles are focused on Regional Growth, Customer Experience and Digital Transformation.

GIG Gulf has created a diverse and inclusive working environment and culture with a workforce of over 800 employees, with over 60 nationalities, across 15 branches and retail shops region-wide and over 1 million customers. GIG Gulf is a caring partner that encourages customers to achieve their goals and live an inspiring and fulfilling life. We are obsessed with customer feedback and continuously evolving to become the region’s digital insurer of reference, committed to running our operations in a responsible, sustainable way.

Job purpose:

Are you passionate about turning Artificial Intelligence from experimentation into measurable business value?

As an AI Engineer, you will play a hands‑on role in designing, building, deploying, and operating enterprise‑grade AI solutions that support GIG Gulf's AI Adoption agenda. You will work closely with technology teams, data professionals, security teams, and external partners to create AI‑enabled products, intelligent automation capabilities, GenAI solutions, AI agents, and decision-support systems that are secure, scalable, compliant, and production‑ready.

The role supports bridging the gap between AI innovation and business outcomes by developing solutions that improve customer experience, operational efficiency, employee productivity, risk management, and decision‑making across the organization

As a AI Engineer, you will work closely with business and IT stakeholders to:

• develop and evolve business AI solutions
• lead pilots, POCs and exploration of new innovative solutions, practices and patterns
• design and deliver cloud‑based and AI‑enabled solutions that are secure, scalable, and fit for purpose
• actively contribute to the organization’s AI delivery priorities, ensuring alignment with business outcomes, regulatory requirements, and operational realities

Key Responsibilities:

In collaboration with GIG Gulf business and IT stakeholders and considering information system landscape, business ambitions, recommendation, best practices, technology evolution and market trends:

AI Enablement

• Work with architecture, data, and business teams to translate business problems into AI‑enabled solutions.
• Assist in evaluating emerging AI technologies, frameworks, platforms, and vendor offerings.
• Promote reuse of enterprise AI capabilities, patterns, and shared services.

AI Solution Engineering

• Design and develop AI, GenAI, and Agentic AI solutions.
• Build intelligent applications leveraging LLMs, SLMs, AI Agents, RAG architectures, and enterprise AI platforms.
• Develop AI‑enabled workflows, copilots, chatbots, search experiences, document intelligence solutions, and automation use cases.
• Create reusable AI components, accelerators, and development standards.
• Implement retrieval architectures using vector databases, embedding models, and knowledge repositories.
• Ensure AI solutions leverage approved and governed enterprise data sources.
• Collaborate with Data Architecture and Integration teams to establish scalable AI foundations.

AI Operations (LLMOps / MLOps)

• Deploy AI workloads using enterprise cloud platforms including Azure and AWS.
• Establish automated DevOps processes.
• Monitor model performance and support lifecycle management, versioning, evaluation, and continuous improvement.

Governance, Security & Responsible AI

• Ensure compliance with enterprise AI governance frameworks and policies.
• Embed security, auditability and accountability controls into AI solutions.
• Implement safeguards against prompt injections, data leakage, model abuse and adversarial attacks.
• Lead pilots, proofs of concept, and experimentation initiatives for emerging AI technologies.
• Assess new AI capabilities and provide recommendations based on business value and risk.
• Contribute to development of AI engineering standards, frameworks, and reusable assets.
• Stay current on advancements in GenAI, Agentic AI, LLMs, foundation models, AI infrastructure, and industry trends.

Operational & Technical Responsibilities:

Function as an active hands‑on AI Engineer for enterprise and business initiatives:

• Develop AI solutions using Python, low code application development and modern AI frameworks.
• Build and optimize prompts, workflows, orchestration layers, and agent behaviors.
• Develop solutions leveraging approved AI services (e.g. OpenAI, Azure AI, AWS AI, Anthropic, Google).
• Implement semantic search, retrieval augmentation, knowledge grounding, and contextual reasoning solutions.

Generative AI & Agentic AI Solutions

Design and implement enterprise‑grade GenAI solutions including:

• Retrieval Augmented Generation (RAG)
• AI copilots and assistants
• Automation and decision‑support systems

Quality, Testing & Evaluation

• Structured testing of AI outputs, hallucination management, and response quality controls.
• Continuously improve model performance and user experience.

Knowledge Management & Documentation

• Maintain technical documentation, architecture diagrams, model cards, and operational procedures.

Business / Domain knowledge requirements (desirable)

• Understanding of regulatory considerations affecting AI deployment in financial services and insurance.
• Familiarity with data privacy, residency, and compliance requirements within UAE and GCC markets.
• Basic knowledge of the insurance business

Role Requirements:

• Bachelor of Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Systems, or related discipline.
• 3-5 years of experience in software engineering, cloud engineering, machine learning, Automation or AI.
• 1 - 2 years of hands‑on experience implementing AI or ML solutions.
• Experience building and deploying cloud‑native applications or automations.
• Demonstrated experience delivering business‑focused technology solutions.
• Ability to design, develop, deploy, monitor, and operate production‑grade AI solutions.
• Python Development and automation
• Ability to build scalable AI applications and integrations.
• Generative AI
• Experience with:
• LLM such as Anthropic Claude, OpenAI, Google Gemini, Azure OpenAI
• Agent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, AWS Agentcore, Google ADK, Microsoft Agent Framework
• RAG and retrieval: vector databases (such as Pinecone, pgvector, Qdrant), semantic search and embeddings
• Workflow orchestration, automation and/or other intelligent automation tooling
• Prompt Engineering
• Cloud Engineering and hands‑on experience using Azure and/or AWS for AI workloads, cross‑cloud deployment, IaC (such as Terraform, Pulumi), CI/CD pipelines
• Ability to design, develop, deploy, monitor, and operate production‑grade AI solutions.
• Python Development and automation
• Ability to build scalable AI applications and integrations.
• Generative AI
• Experience with:
• LLM such as Anthropic Claude, OpenAI, Google Gemini, Azure OpenAI
• Agent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, AWS Agentcore, Google ADK, Microsoft Agent Framework
• RAG and retrieval: vector databases (such as Pinecone, pgvector, Qdrant), semantic search and embeddings
• Workflow orchestration, automation and/or other intelligent automation tooling
• Prompt Engineering
• Cloud Engineering and hands‑on experience using Azure and/or AWS for AI workloads, cross‑cloud deployment, IaC (such as Terraform, Pulumi), CI/CD pipelines
• Good stakeholder management skills across business, IT, and control functions
• Ability to communicate technical topics clearly
• Comfortable working in a high‑demand, delivery‑oriented environment

Communication and Soft Skills

• Excellent communication skills in English, both verbal and written
• Team player – ability to work with a team and influence a positive collaborative culture
• Ability to prioritize workload appropriately based on the impact on the business
• Demonstrated ability to work independently while efficiently managing multiple projects simultaneously.