52 AI Intern jobs in Qatar

AI Trainers Wanted in Qatar

We're growing our AI training programs and looking for freelance trainers who can show professionals how to use AI in real work —

Sales
• HR
• Finance
• Project Management
• Marketing

If you can help people say,

"Now I really understand how to use AI at work" — we'd love to hear from you.

Location:
Doha, Qatar

Type
: Freelance / Workshop-based

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AI Trainers Wanted in Qatar

Excellence Training Centre is expanding its AI Training Programs and we're looking for freelance trainers who can help professionals apply AI tools in real-world work scenarios across; Sales, HR, Finance, Project Management, Marketing

If you can empower learners to say —

"Now I really understand how to use AI at work" — we'd love to connect with you.

Location: Doha, Qatar

Type: Freelance / Workshop-based

Send your resume to

Job Type: Part-time

At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company where product innovation and mature software engineering are embedded in our core DNA. Our core values of Respect, Fairness, Growth, Agility, and Inclusiveness guide everything we do. We continually expand our expertise in digital strategy, design, architecture, and product management to offer measurable results and outside-the-box thinking.

About the Role

We are seeking a highly skilled and experienced Senior AI Engineer a deep understanding of asset-heavy industries such as oil & gas, manufacturing, or utilities to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions.

You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems.

Responsibilities

Generative AI Pipeline Development

• • Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads.
• Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs.
• Build CI/CD pipelines with integrated prompt regression testing and version control.
• Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows.
• Monitor system performance using tools like Langfuse or Prometheus.

Data and Document Ingestion

• • Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data.
• Apply preprocessing pipelines for text, images, and code.
• Ensure data integrity, format consistency, and security across sources.

AI Service Integration

• • Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.).
• Build internal APIs for smooth backend-AI communication.
• Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets.
• Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy.

Retrieval-Augmented Generation (RAG) Pipelines

• • Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API).
• Design custom retrieval strategies for multi-modal or multi-source documents.
• Apply post-retrieval ranking using DPO or feedback-based techniques.
• Improve contextual relevance through re-ranking, chunk merging, and scoring logic.

LLM Integration and Optimization

• • Manage prompt engineering, model interaction, and tuning workflows.
• Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design.
• Optimize generation using temperature tuning, token limits, and speculative decoding.
• Integrate observability and cost-monitoring into LLM workflows.

Backend Services Ownership

• • Design and maintain scalable backend services supporting GenAI applications.
• Implement monitoring, logging, and performance tracing.
• Build RBAC (Role-Based Access Control) and multi-tenant personalization.
• Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production.

Required Skills and Qualifications

Education

• Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or related field.

Experience

• • 5+ years of experience in AI/ML engineering with end-to-end pipeline development.
• Hands-on experience building and deploying LLM/RAG systems in production.
• Strong experience with public cloud platforms (AWS, Azure, or GCP).
• 2+ years of experience in asset-heavy industries (e.g., oil & gas, utilities, manufacturing).

Technical Skills

• • Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch.
• Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph.
• Experience with RESTful API development and version control using Git.
• Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval.
• Familiarity with Docker, Kubernetes, and scalable microservice design.
• Experience with observability tools like Prometheus, Grafana, or Langfuse.

Generative AI Specific Skills

• • Knowledge of LLMs, VAEs, Diffusion Models, GANs.
• Experience building structured + unstructured RAG pipelines.
• Prompt engineering with safety controls, schema enforcement, and hallucination mitigation.
• Experience with prompt testing, caching strategies, output filtering, and fallback logic.
• Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods.

Soft Skills

• • Strong analytical, problem-solving, and debugging skills.
• Excellent collaboration with cross-functional teams: product, QA, and DevOps.
• Ability to work in fast-paced, agile environments and deliver production-grade solutions.
• Clear communication and strong documentation practices.

Preferred Qualifications

• • Experience with OCR, document parsing, and layout-aware chunking.
• Hands-on with MLOps and LLMOps tools for Generative AI.
• Contributions to open-source GenAI or AI infrastructure projects.
• Knowledge of GenAI governance, ethical deployment, and usage controls.
• Experience with hallucination suppression frameworks like , Rebuff, or Constitutional AI.

• Meaningful and interesting projects delivered to leaders of industry across oil and gas and emerging energy sectors
• Commitment to Diversity and Inclusion ; we are an organisation actively committed to diversity and inclusion across our business with employee networks committed to giving all employees a voice
• Global connections : join experts around the world who are at the leading edge of our industry, shaping the standards of our profession

• Research current AI applications in asset integrity (e.g., predictive modeling, anomaly detection).
• Identify inefficiencies in existing workflows and propose AI-based solutions.
• Interview team members to understand data availability and operational challenges.
• Develop 2-3 AI use cases with feasibility assessments.

• A research report or white paper.
• A presentation summarizing findings and recommendations.
• A simple prototype or mock-up (optional).

• Bachelor's degree (or final year student) in Engineering, Computer Science, Data Science, or a related field.
• Strong analytical and research skills.
• Basic understanding of AI/ML concepts and tools.
• Ability to communicate technical findings clearly.

• Familiarity with Python, MATLAB, or other data analysis tools.
• Exposure to asset integrity or reliability engineering concepts.
• Experience with data visualization.

• Research and innovation in AI applications.
• Technical writing and presentation skills.
• Exposure to real-world engineering challenges.

Job Description: Lead AI Strategist (Technical)

Driving AI Transformation Across Diversified Business Verticals

Position: Lead AI Strategist (Technical)

Role Overview

We are seeking a forward-thinking, technically adept AI Strategist to spearhead our AI and RPA (Robotic Process Automation) initiatives at the enterprise level. As the lead AI Strategist, you will collaborate across all business functions to identify, plan, and execute AI-driven transformation projects, ensuring measurable improvements in both business outcomes and employee productivity. This position is tailored for a hands-on strategist with a strong technical foundation in AI platforms, RPA, data analytics, and ERP systems, who can serve as a bridge between business strategy and technical execution.

Key Responsibilities

• AI & RPA Roadmap Development: Design, implement, and refine a comprehensive AI and RPA strategy aligned with company objectives, business unit needs, and evolving market trends.
• Cross-Departmental Collaboration: Engage with stakeholders across diverse business units—including automotive, IT, energy, geo and material testing, logistics, travel, engineering, retail, and all back-office functions—to understand department-specific use cases and pain points.
• Business Use Case Identification: Work closely with department heads and process owners to identify high-impact AI and RPA opportunities that address both operational efficiency and employee productivity.
• Solution Architecture & Technical Leadership: Lead the design and implementation of AI/ML models, RPA solutions, and data analytics platforms. Ensure all technical solutions are scalable, secure, and aligned with the company's IT architecture.
• ERP Integration: Identify opportunities to leverage AI and automation within ERP systems, enhancing core business processes such as HR, finance, legal, supply chain, and customer relationship management.
• Change Management: Develop strategies to facilitate digital transformation, including employee training, communication, and adoption of AI-driven solutions.
• Performance Measurement: Define KPIs and success metrics for all AI/RPA projects. Track ROI, productivity gains, and business impact, reporting progress to executive leadership.
• Continuous Learning & Innovation: Stay abreast of the latest developments in AI, RPA, data analytics, and Gen C technologies. Foster a culture of experimentation and innovation within teams.
• Vendor & Partner Management: Evaluate and manage relationships with third-party vendors and technology partners, ensuring solutions are cost-effective and future-ready.
• Risk Management & Compliance: Ensure all AI and automation deployments comply with internal policies, industry standards, and relevant legal or ethical guidelines.

Desired Skills & Qualifications

• Education: Bachelor's or Master's degree in computer science, Engineering, or a related technical discipline.
• Experience:
• Minimum 7 years of professional experience in AI, machine learning, data analytics, robotic process automation, or related technical business application fields.
• At least 2 years of experience in a strategic role, leading AI initiatives, defining AI roadmaps, and aligning AI solutions with business objectives.
• Technical Proficiency:
• Strong foundation in AI/ML platforms, including generative AI, natural language processing (NLP), computer vision, and deep learning.
• Proven experience overseeing AI/ML and robotic process automation (RPA) solution deployment, with direct involvement in architecting integration strategies.
• In-depth understanding of ERP systems, their data structures, and how AI and automation can augment business processes.
• Proficiency in integrating AI solutions with enterprise software such as Oracle and SAP, ensuring robust data flows and operational impact.
• Skilled in using advanced data analytics and visualization tools, including Power BI, Tableau, and others, to drive actionable business insights and strategic decisions.

Business Acumen
: Experience working across diverse industries and business functions—including automotive, IT, energy, logistics, engineering, retail, and back-office functions. Ability to translate business challenges into technical solutions.

Project Management
: Proven ability to lead cross-functional teams, manage multiple projects simultaneously, and deliver results on time and within budget.

Communication & Stakeholder Management
: Excellent communication, presentation, and interpersonal skills. Ability to influence and collaborate effectively with technical and non-technical stakeholders at all levels.

Change Leadership
: Experience driving cultural and operational change in complex organizations. Adept at managing resistance and fostering buy-in for digital transformation initiatives.

Adaptability
: Comfortable working in a dynamic, fast paced, and multi-disciplinary environment.

Certifications (Preferred):
Relevant certifications in AI, RPA, enterprise architecture, and project management are highly advantageous.

Key Performance Indicators (KPIs)

• Number of AI/RPA initiatives successfully launched and scaled across business units
• Measured improvements in business process efficiency and employee productivity
• ROI and business impact of implemented AI solutions
• User adoption rates and satisfaction with AI-driven tools
• Up-skilling and enablement of internal teams in AI and automation practices

Opportunities & Challenges

• Opportunities: This role offers the chance to architect and influence the AI journey of a large, multifaceted organization, working with passionate teams and leveraging a vast array of data and business processes.
• Challenges: Navigating complex legacy systems, diverse stakeholder needs, and ensuring organization-wide alignment in a rapidly evolving technological landscape.

Reporting Line

This position reports directly to the Group IT Director. As the primary point of contact for AI and RPA strategy within the company, the Lead AI Strategist will collaborate closely with the Group IT Director to ensure alignment with organizational priorities, technical standards, and security protocols. The role involves ongoing collaboration through regular updates, strategic planning sessions, and performance evaluations to support and drive the company's enterprise-wide AI transformation efforts.

Nair Systems is currently looking for Azure AI Engineer for Qatar

Skill Set:

Should have experience in Databricks, AI foundry, machine learning, AI speech, Cosmos DB, API management, OpenAI integration, Azure Kubernetes service.

Should have experience in Infrastructure Security and the candidate should have past experience on Infrastructure Support

should be Azure AI Certified

Should you be interested in this opportunity, please send your latest resume in MS Word format at the earliest

Remarkable people, trusted by clients to design and advance the world

Wood is currently hiring for a AI Research Intern to support future growth in our expanding business

This is a 3 month Internship based in Qatar.

AI Research Intern will Join Wood PLC's Asset Life Optimisation consulting team to dive into the intersection of artificial intelligence and asset integrity. This internship focuses on exploring how AI and machine learning can enhance service delivery in corrosion, vibration, and integrity management.

Designing the future. Transforming the world

Reflecting the market focus for the office in both brownfield and green field opportunities, multi-skilled personnel are sought, in particular those with experience in:

Onshore Oil and Gas

Offshore Oil and Gas

What we can offer

• Meaningful and interesting projects delivered to leaders of industry across oil and gas and emerging energy sectors
• Commitment to Diversity and Inclusion ; we are an organisation actively committed to diversity and inclusion across our business with employee networks committed to giving all employees a voice
• Global connections : join experts around the world who are at the leading edge of our industry, shaping the standards of our profession

Key Responsibilities:

• Research current AI applications in asset integrity (e.g., predictive modeling, anomaly detection).
• Identify inefficiencies in existing workflows and propose AI-based solutions.
• Interview team members to understand data availability and operational challenges.
• Develop 2–3 AI use cases with feasibility assessments.

Deliverables:

• A research report or white paper.
• A presentation summarizing findings and recommendations.
• A simple prototype or mock-up (optional).

What makes you remarkable?

At Wood, we are committed to equal opportunities and welcome all talented individuals to consider joining our team. So even if you don't match every statement below but feel you have some of the experience, knowledge or skills needed for this role, we encourage you to apply. It will take all of us working together to deliver solutions to the world's most critical challenges.

Experience:

• Bachelor's degree (or final year student) in Engineering, Computer Science, Data Science, or a related field.
• Strong analytical and research skills.
• Basic understanding of AI/ML concepts and tools.
• Ability to communicate technical findings clearly.

Preferred Qualifications:

• Familiarity with Python, MATLAB, or other data analysis tools.
• Exposure to asset integrity or reliability engineering concepts.
• Experience with data visualization.

Learning Opportunities:

• Research and innovation in AI applications.
• Technical writing and presentation skills.
• Exposure to real-world engineering challenges.

Wood is a global leader in consulting and engineering, helping to unlock solutions to critical challenges in energy and materials markets. We provide consulting, projects and operations solutions in 60 countries, employing around 35,000 people.

Diversity Statement

We are an equal opportunity employer that recognises the value of a diverse workforce. All suitably qualified applicants will receive consideration for employment on the basis of objective criteria and without regard to the following (which is a non-exhaustive list): race, colour, age, religion, gender, national origin, disability, sexual orientation, gender identity, protected veteran status, or other characteristics in accordance with the relevant governing laws.

Nair Systems is currently looking for AI Azure Engineer for Qatar

Skill Set:

Should have experience in Infrastructure Security and the candidate should have past experience on Infrastructure Support

should be Azure AI Certified

Required Skills & Expertise:

·   Azure AI Engineering

·   Databricks

·   Azure AI Foundry

·   Machine Learning

·   AI Speech Services

·   Cosmos DB

·   API Management

·   OpenAI Integration

·   Azure Kubernetes Service (AKS)

Should you be interested please send resume

• Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
• 2–3 years of experience in AI development, data analytics, or related projects.
• Proficiency in Python.
• Experience with machine learning libraries and frameworks
• Familiarity with cloud-based AI platforms
• Basic knowledge of data visualization tools.
• Understanding of prompt engineering and large language model (LLM) concepts.

Preferred Skills:

• Hands-on experience with generative AI tools
• Familiarity with AI-powered automation tools.
• Knowledge of data processing tools.
• Awareness of ethical AI, privacy, and security principles.
• Exposure to MLOps practices is an advantage.

Job Type: Full-time