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MASTER-WORKS

<div><p>About the Role:</p><p>
Master works is looking for an experienced <b>LLM Engineer</b> to join our team working on next-generation AI-driven analytics solutions. The ideal candidate will design and implement natural language search, semantic search solutions, and generative AI features for our web applications. You will work hands-on with advanced language models, vector databases, RAG pipelines, and build intelligent workflows to enable actionable insights from both structured and unstructured data.</p><p><b>
Key Responsibilities:</b></p><ul><li>
Develop and maintain natural language search capabilities and semantic search solutions using vector databases.</li><li>
Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.</li><li>
Build and optimize Generative AI features (summarization, recommendations, insights) for analytics applications.</li><li>
Design and implement Agents and Workflows for complex tasks across datasets.</li><li>
Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.</li><li>
Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.</li><li>
Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.</li><li>
Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.</li><li>
Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.
</li></ul><p><b>Required Qualifications &amp; Skills:</b></p><ul><li>
Bachelor's or master's degree in computer science, AI/ML, Data Science, or related field.</li><li>
Hands-on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).</li><li>
Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.</li><li>
Strong understanding of embeddings, semantic search, and their practical applications.</li><li>
Expertise in RAG pipelines, Agents, and Workflow orchestration.</li><li>
Proficiency in Python and relevant AI/ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow).</li><li>
Familiarity with NL-to-SQL systems and natural language query processing.</li><li>
Experience working with structured and unstructured data sources.</li><li>
Knowledge of data pipelines, preprocessing, and storage formats for analytics.</li><li>
Ability to design scalable, production-ready AI solutions integrated with web applications.</li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Experience working with AI based chatbots, Natural language search, NL to SQL.</li><li>
Knowledge of prompt engineering and fine-tuning LLMs.</li><li>
Familiarity with data privacy, security, and compliance considerations in AI pipelines.</li></ul><p><b>
Soft Skills:</b></p><ul><li>
Strong problem-solving and analytical skills.</li><li>
Excellent communication skills to work with cross-functional teams.</li><li>
Passion for AI and staying up to date with the latest developments in LLMs and generative AI.</li></ul></div>

LLM engineer

Master Works

<div>
 About the Role:
 <br/>
 <br/>
 Master works is looking for an experienced
 <strong>
  LLM Engineer
 </strong>
 to join our team working on next-generation AI-driven analytics solutions. The ideal candidate will design and implement natural language search, semantic search solutions, and generative AI features for our web applications. You will work hands-on with advanced language models, vector databases, RAG pipelines, and build intelligent workflows to enable actionable insights from both structured and unstructured data.
 <br/>
 <br/>
 <strong>
  Key Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop and maintain natural language search capabilities and semantic search solutions using vector databases.
  </li>
  <li>
   Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.
  </li>
  <li>
   Build and optimize Generative AI features (summarization, recommendations, insights) for analytics applications.
  </li>
  <li>
   Design and implement Agents and Workflows for complex tasks across datasets.
  </li>
  <li>
   Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.
  </li>
  <li>
   Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.
  </li>
  <li>
   Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.
  </li>
  <li>
   Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.
  </li>
  <li>
   Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications &amp; Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's or master's degree in computer science, AI/ML, Data Science, or related field.
  </li>
  <li>
   Hands-on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).
  </li>
  <li>
   Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
  </li>
  <li>
   Strong understanding of embeddings, semantic search, and their practical applications.
  </li>
  <li>
   Expertise in RAG pipelines, Agents, and Workflow orchestration.
  </li>
  <li>
   Proficiency in Python and relevant AI/ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow).
  </li>
  <li>
   Familiarity with NL-to-SQL systems and natural language query processing.
  </li>
  <li>
   Experience working with structured and unstructured data sources.
  </li>
  <li>
   Knowledge of data pipelines, preprocessing, and storage formats for analytics.
  </li>
  <li>
   Ability to design scalable, production-ready AI solutions integrated with web applications.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience working with AI based chatbots, Natural language search, NL to SQL.
  </li>
  <li>
   Knowledge of prompt engineering and fine-tuning LLMs.
  </li>
  <li>
   Familiarity with data privacy, security, and compliance considerations in AI pipelines.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Soft Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong problem-solving and analytical skills.
  </li>
  <li>
   Excellent communication skills to work with cross-functional teams.
  </li>
  <li>
   Passion for AI and staying up to date with the latest developments in LLMs and generative AI.
  </li>
 </ul>
</div>


Brainlake Advertising LLC

<p></p><div><p>Seeking a high-performing Prompt &amp; Agent Engineer (Senior Associate / Manager) to join a fast-paced engagement on-site in Doha, Qatar. This is a 3-month contract, extendable based on performance and project needs.</p><p>
The primary purpose of the role is to rapidly design, build, and deploy AI agents and prompt-engineered solutions for different use cases. You will work hands-on with large language models &mdash; particularly Google Gemini &mdash; to develop production-ready agents that automate workflows, enhance citizen services, and drive operational efficiency across certain initiatives</p><p></p><ul>
<li>
Agent Development - Design, build, and deploy AI agents using Google Gemini and related frameworks to automate workflows and service delivery processes</li>
<li>Prompt Engineering - Craft, test, and optimize advanced prompts and prompt chains to maximize LLM output quality, accuracy, and reliability for production use cases
</li><li>Rapid Prototyping - Quickly build functional prototypes and MVPs of AI-powered tools, iterating fast based on stakeholder feedback and real-world testing</li>
<li>Integration and Orchestration - Connect AI agents with APIs, databases, and existing government systems using orchestration tools such as LangChain, Vertex AI Agent Builder, or similar frameworks</li>
<li>Evaluation and Testing - Develop evaluation benchmarks, test suites, and guardrails to ensure agent outputs are accurate, safe, and aligned with compliance requirements</li>
<li>Knowledge Transfer - Document agent architectures, prompt libraries, and best practices. Support internal teams in adopting and maintaining deployed solutions</li>
<li>Stakeholder Collaboration - Work closely with project leads, solution architects, and government stakeholders to translate business requirements into AI agent specifications and deliverables</li>
</ul><p><b>
Requirements</b></p><p></p><ul>
<li>
3-5 years of hands-on experience in AI/ML engineering, prompt engineering, or agent development with a strong bias for speed and execution</li>
<li>Demonstrated experience building agents and applications using Google Gemini (required), with familiarity in Vertex AI, Gemini API, and Agent Builder</li>
<li>Strong programming skills in Python with experience in LLM orchestration frameworks (LangChain, Llama Index, or equivalent)</li>
<li>Experience with RAG architectures, function calling, tool use, and multi-agent systems</li>
<li>Ability to work on-site in Doha, Qatar for the full engagement duration (3 months, extendable)</li>
<li>Fast learner who thrives under pressure with a ship-fast, iterate-fast mentality</li>
<li>Public sector or government consulting experience is a plus (Arabic is a plus)</li>
<li>Google Cloud or AI-related certifications are a bonus</li></ul></div>

Prompt and Agent Engineer

Brainlake

<div>
 Seeking a high-performing Prompt &amp; Agent Engineer (Senior Associate / Manager) to join a fast-paced engagement on-site in Doha, Qatar. This is a 3-month contract, extendable based on performance and project needs.
 <br/>
 <br/>
 The primary purpose of the role is to rapidly design, build, and deploy AI agents and prompt-engineered solutions for different use cases. You will work hands-on with large language models &mdash; particularly Google Gemini &mdash; to develop production-ready agents that automate workflows, enhance citizen services, and drive operational efficiency across certain initiatives
 <br/>
 <br/>
 <ul>
  <li>
   Agent Development - Design, build, and deploy AI agents using Google Gemini and related frameworks to automate workflows and service delivery processes
  </li>
  <li>
   Prompt Engineering - Craft, test, and optimize advanced prompts and prompt chains to maximize LLM output quality, accuracy, and reliability for production use cases
  </li>
  <li>
   Rapid Prototyping - Quickly build functional prototypes and MVPs of AI-powered tools, iterating fast based on stakeholder feedback and real-world testing
  </li>
  <li>
   Integration and Orchestration - Connect AI agents with APIs, databases, and existing government systems using orchestration tools such as LangChain, Vertex AI Agent Builder, or similar frameworks
  </li>
  <li>
   Evaluation and Testing - Develop evaluation benchmarks, test suites, and guardrails to ensure agent outputs are accurate, safe, and aligned with compliance requirements
  </li>
  <li>
   Knowledge Transfer - Document agent architectures, prompt libraries, and best practices. Support internal teams in adopting and maintaining deployed solutions
  </li>
  <li>
   Stakeholder Collaboration - Work closely with project leads, solution architects, and government stakeholders to translate business requirements into AI agent specifications and deliverables
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3-5 years of hands-on experience in AI/ML engineering, prompt engineering, or agent development with a strong bias for speed and execution
  </li>
  <li>
   Demonstrated experience building agents and applications using Google Gemini (required), with familiarity in Vertex AI, Gemini API, and Agent Builder
  </li>
  <li>
   Strong programming skills in Python with experience in LLM orchestration frameworks (LangChain, Llama Index, or equivalent)
  </li>
  <li>
   Experience with RAG architectures, function calling, tool use, and multi-agent systems
  </li>
  <li>
   Ability to work on-site in Doha, Qatar for the full engagement duration (3 months, extendable)
  </li>
  <li>
   Fast learner who thrives under pressure with a ship-fast, iterate-fast mentality
  </li>
  <li>
   Public sector or government consulting experience is a plus (Arabic is a plus)
  </li>
  <li>
   Google Cloud or AI-related certifications are a bonus
  </li>
 </ul>
</div>


TAWANTECH

<div>
 <strong>
  Job Summary:
  <br/>
  <br/>
 </strong>
 We are looking for a Machine Learning Engineer with 4+ years of experience in building, deploying, and optimizing ML models in software environments. The ideal candidate has strong Python skills and hands-on experience delivering production-ready ML solutions.
 <br/>
 <br/>
 <strong>
  Key Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop, train, and deploy machine learning models.
  </li>
  <li>
   Build scalable data pipelines and integrate ML into applications.
  </li>
  <li>
   Perform data preprocessing, feature engineering, and model evaluation.
  </li>
  <li>
   Monitor model performance and implement improvements.
  </li>
  <li>
   Collaborate with engineering and product teams in agile environments
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's or Master's in Computer Science, AI, or related field.
  </li>
  <li>
   4+ years of ML experience in software/product companies.
  </li>
  <li>
   Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
  </li>
  <li>
   Experience deploying models in production (cloud preferred: AWS/Azure/GCP).
  </li>
  <li>
   Good understanding of statistics, algorithms, and MLOps practices
  </li>
 </ul>
</div>


Machine Learner Engineer

Hudhud Maps

<div><p><b>About The Role:</b></p><p>
We are looking for a <b>Senior Machine Learning Engineer</b> with deep expertise in <b>Natural Language Processing (NLP)</b> and <b>Large Language Models (LLMs)</b> to join our growing team. This role requires strong research-to-production skills, combined with robust software engineering capabilities to ensure scalable, reliable systems.</p><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3>
<ul><li>Design, develop, and deploy <b>NLP and LLM-based solutions</b> for real-world applications.</li><li>
Translate research papers and experimental models into <b>production-ready systems</b>.</li><li>
Architect and implement scalable ML pipelines, ensuring performance and reliability.</li><li>
Collaborate with product and engineering teams to integrate ML models into Hudhud's platforms.</li><li>
Conduct experiments, evaluate models, and optimize for accuracy, efficiency, and cost.</li><li>
Stay up to date with the latest advancements in NLP, LLMs, and generative AI.</li><li>
Guide junior engineers and contribute to building a high-performance AI team.</li></ul><p></p><h3 class="jobSectionHeader"><b>
Qualifications &amp; Skills</b></h3>
<ul><li><b>Education:</b> MSc or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related fields.</li><li><b>
Experience:</b> Minimum 5+ years of professional experience in ML/NLP, with at least 3+ years working on LLMs.</li><li><b>
Core Expertise:</b><ul><li>
Strong background in <b>NLP techniques</b> (transformers, embeddings, sequence models).</li><li>
Hands-on experience with <b>LLMs</b> (fine-tuning, prompt engineering, model evaluation).</li><li>
Practical experience with <b>LangChain</b> and/or <b>Haystack</b> frameworks for building LLM-powered applications.</li><li>
Solid understanding of <b>ML system design</b> and deployment in production environments.</li></ul></li><li><b>
Software Engineering Skills:</b><ul><li>
Proficiency in <b>Python</b> and ML frameworks (PyTorch, TensorFlow, Hugging Face).</li><li>
Strong knowledge of <b>software engineering principles</b> (version control, testing, CI/CD).</li><li>
Experience with <b>distributed systems, APIs, and microservices</b>.</li><li>
Familiarity with <b>cloud platforms</b> (AWS, GCP, Azure) and containerization (Docker, Kubernetes).</li></ul></li></ul><ul><li><b>
Problem-Solving:</b> Excellent analytical skills and ability to work independently in a fast-paced startup environment.</li><li><b>
Preferred</b>: Experience in Arabic NLP or multilingual LLMs is a strong plus.</li></ul><p></p><p><b>
Joining Hudhud means:</b></p>
<ul><li>Working on <b>real-world problems</b> with direct impact across industries in Saudi Arabia and beyond.</li><li>
Being part of a <b>fast-growing startup</b> that values innovation, ownership, and bold ideas.</li><li>
Collaborating with a team passionate about <b>pushing the boundaries of geospatial technology</b>.</li><li>
Helping shape the future of <b>customer experience through maps and location intelligence</b>.</li></ul>
<p>We're not just building technology &mdash; we're redefining how people and businesses experience the world around them.</p></div>

Senior Machine Learning Engineer (NLP/LLMs)

Tabby

<div><h3 class="jobSectionHeader"><b>Description</b></h3><div><br>
Tabby builds financial products used by millions of users across the GCC. Alongside core fintech products, we are actively building internal platforms for AI agents and LLM-based automation used across the company.<br>
</div><div>This internship is not educational by default. It is an engineering-adjacent role with real production impact.</div><div>
The AI Agents Platform team builds an internal platform that allows teams across Tabby to create, run, evaluate, and iterate on AI agents. These agents automate real human workflows: customer support, operations, fraud checks, data validation, and internal tooling.<br>
</div><div>The platform is young, evolving fast, and already used by multiple teams. The internship is designed for candidates who are comfortable working in ambiguous, experimental environments and can think in systems rather than isolated tasks.</div><h3 class="jobSectionHeader"><b><br>
Key Responsibilities</b></h3><div><br>
This is not a demo or experimentation-only role. Interns work on real agents, workflows, and internal tools.<br>
</div><ul><li>Build AI agents and automations using internal no-code and low-code tooling</li>
<li>Configure agent workflows, tools, and orchestration logic</li>
<li>Integrate agents with internal systems via APIs and tools</li>
<li>Participate in designing agent architectures and workflows</li>
<li>Help test, evaluate, and iterate on agent behavior and quality</li>
<li>Work with datasets and evaluation results to improve agent performance</li>
<li>Document agent logic, workflows, and best practices</li>
<li>Work closely with platform engineers, product managers, and internal users</li></ul><br>
<h3 class="jobSectionHeader"><b>
Skills, Knowledge &amp; Expertise</b></h3><br>
<ul>
<li>
Strong logical and systems thinking</li>
<li>Ability to break down human workflows into structured steps</li>
<li>Understanding of how web services, APIs, and tools interact</li>
<li>Experience with no-code or low-code platforms</li>
<li>Basic understanding of data formats (JSON), APIs, and webhooks</li>
<li>Ability to reason about edge cases, failure modes, and correctness</li>
<li>High level of ownership and responsibility</li>
<li>Comfort with fast iteration and experimental environments</li>
<li>English sufficient for documentation and team communication</li>
</ul><ul><li>Experience with LLMs, AI agents, or automation</li>
<li>Experience building internal tools or automations</li>
<li>Experience with Python</li>
<li>Education in data science, machine learning field</li>
<li>Understanding of prompt design or agent orchestration concepts</li>
<li>Familiarity with evaluation, testing, or quality metrics</li>
<li>Curiosity about AI system behavior and limitations</li></ul><br>
<h3 class="jobSectionHeader"><b>
Eligibility</b></h3><br>
<ul>
<li>
Saudi nationals only</li>
<li>Internship is structured and administered through HRDF</li>
<li>We welcome both current students and fresh grads</li>
<li>We expect a full-time level of engagement throughout the internship. The program is not part-time: interns should be ready to contribute at a full working-day pace. We understand that students may occasionally need flexibility for classes or exams, which can be aligned with the mentor in advance, but overall performance, ownership, and context involvement are expected at a full-time level.</li>
</ul><ul><li>Paid internship</li>
<li>Full integration into the automations building team</li>
<li>Distributed engineering team across multiple countries</li>
<li>Remote work is available from anywhere</li>
<li>Office-based work is available in Riyadh</li>
<li>Clear path to a junior AI automation, no-code engineer, or platform role based on performance</li>
</ul><div>
<br>
This internship is intentionally demanding and designed for candidates aiming for fast professional growth in AI agents and automation engineering.</div><h3 class="jobSectionHeader"><b><br>
About Tabby</b></h3><div>
Tabby creates financial freedom in the way people shop, earn and save, by reshaping their relationship with money.<br>
<br>
The company&rsquo;s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 32,000 global brands and small businesses, including Amazon, Noon, IKEA and Shein use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.<br>
<br>
Tabby has generated over $7 billion in transaction volume for its partner brands and has the highest rated, most reviewed, largest and fastest growing app of any fintech in the GCC region.<br>
<br>
Tabby launched operations in 2020 and has raised +$1 billion in equity and debt funding from global and regional investors.</div></div>

No-Code / AI Agents Engineering Intern

Explore 448+ Ai engineer in Riyadh this February. Find roles across top companies and apply now to boost your career.

448 ai engineer jobs In Riyadh

LLM engineer

LLM engineer

Prompt and Agent Engineer

Prompt and Agent Engineer

Machine Learner Engineer

Senior Machine Learning Engineer (NLP/LLMs)

No-Code / AI Agents Engineering Intern