sales engineer

production engineer

ai consultant

civil engineer

electrical engineer

ai engineer

Tamara

<div>
 
 Why Tamara?
 
 
 
 We&rsquo;re proud to be Saudi&rsquo;s first FinTech unicorn.
 
 
 Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. &amp; There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration. If this sounds like you: curious, driven, and ready to build, we&rsquo;d love to meet you
 
 
 Apply now and join the next generation of Builders!
 
 
 
 About Tamara's Builders Program
 
 
 
 At Tamara, we believe exceptional talent deserves an exceptional launchpad.
 
 
 Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn&rsquo;t a rotational &ldquo;observer&rdquo; program, it&rsquo;s a career accelerator built for those who want to build, own, and raise the bar early.
 
 
 Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You&rsquo;ll contribute immediately and grow at an accelerated pace.
 
 
 From Product to Engineering, Design to Commercial, you&rsquo;ll tackle meaningful challenges that shape how millions experience fintech across the region. You&rsquo;ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.
 
 
 Our January and June cohorts are your opportunity to move fast, think big, and start building what&rsquo;s next - not someday, but now.
 
 
 
 About The Role
 
 
 
 We&rsquo;re looking for a fresh graduate or early-career
 
 AI Engineer
 
 on a builder track.
 
 
 This role sits between software engineering and applied AI. You will build AI-powered features end-to-end: from turning a product problem into an AI approach, to building pipelines and evaluation, to shipping reliable services in production.
 
 
 You&rsquo;ll work with both
 
 classical ML
 
 and
 
 generative AI
 
 (LLMs, RAG, agents) where they make sense. With the rapid pace of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, privacy, safety, and user impact.
 
 
 
 Your Responsibilities
 
 
 
 <ul>
 <li>
 Build AI products that ship
 </li>
 <ul>
 <li>
 Design and implement AI-powered features and internal tools.
 </li>
 <li>
 Integrate models into real systems (APIs, workflows, dashboards, and operational processes).
 </li>
 </ul>
 <li>
 Work with LLMs in a production-ready way
 </li>
 <ul>
 <li>
 Build retrieval-augmented generation (RAG) pipelines: data sourcing, chunking, embeddings, retrieval, and prompt templates.
 </li>
 <li>
 Build agent-style workflows when needed (tool use, guardrails, and deterministic fallbacks).
 </li>
 </ul>
 <li>
 Own evaluation and quality
 </li>
 <ul>
 <li>
 Define what &ldquo;good&rdquo; means: success metrics, offline tests, and human-in-the-loop review.
 </li>
 <li>
 Set up evaluations for quality, safety, latency, and cost.
 </li>
 </ul>
 <li>
 Make AI reliable and safe
 </li>
 <ul>
 <li>
 Add observability: logging, tracing, and monitoring for quality regressions.
 </li>
 <li>
 Implement privacy and security controls (PII handling, access control, redaction where needed).
 </li>
 <li>
 Participate in incident response and postmortems when AI systems misbehave.
 </li>
 </ul>
 <li>
 Partner across teams
 </li>
 <ul>
 <li>
 Work with product, data, design, and engineering stakeholders to translate messy problems into measurable solutions.
 </li>
 <li>
 Collaborate with platform teams to use existing data pipelines, event streams, and AI tooling responsibly.
 </li>
 </ul>
 <li>
 Use AI tools thoughtfully
 </li>
 <ul>
 <li>
 Use AI assistants for prototyping, debugging, and documentation.
 </li>
 <li>
 Validate outputs, document assumptions, and protect sensitive data.
 
 </li>
 </ul>
 </ul>
 
 Your expertise (must have)
 
 
 
 Fresh graduate or &lt; 1 year of relevant experience (internships and projects count).
 <li>
 Solid programming fundamentals in Python (preferred) or another language used for backend services.
 </li>
 <li>
 Strong foundations in:
 </li>
 <ul>
 <li>
 Software engineering basics (APIs, testing, reliability)
 </li>
 <li>
 Data handling (SQL and/or dataframes)
 </li>
 <li>
 ML/AI fundamentals (training vs. inference, evaluation, overfitting intuition)
 </li>
 </ul>
 <li>
 Clear communication and a collaborative approach.
 
 </li>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Hands-on experience with LLMs and/or RAG from projects (LangChain/LlamaIndex or similar patterns).
 </li>
 <li>
 Familiarity with model serving and deployment (REST/gRPC services, batch jobs, streaming consumers).
 </li>
 <li>
 Exposure to MLOps concepts (experiment tracking, model registry, monitoring).
 </li>
 <li>
 Familiarity with vector databases, search, or information retrieval.
 </li>
 <li>
 Understanding of responsible AI, privacy, and security (PII handling, access control, prompt injection awareness).
 </li>
 <li>
 Experience using AI assistants responsibly for coding and analysis.
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 <ul>
 <li>
 You ship at least one AI feature or internal tool that is used by real users.
 </li>
 <li>
 You set up a simple evaluation and monitoring loop so the system improves over time.
 </li>
 <li>
 Your solutions balance quality, latency, and cost, with clear tradeoffs.
 </li>
 <li>
 When the AI output is wrong or risky, you can debug, mitigate, and explain why.
 
 
 </li>
 </ul>
 All qualified individuals are encouraged to apply.
</div>

Associate AI Engineer - Builders Program

whj.ai وهج

<div>
 
 About Us
 
 
 At whj.ai, we are pushing the boundaries of what's possible with artificial intelligence. We are currently expanding our Research &amp; Development team and are looking for passionate problem-solvers to help us innovate, experiment, and build with Large Language Models (LLMs).
 
 
 
 
 
 The Role
 
 
 We are hiring for our R&amp;D and LLM team! Whether you are a brilliant junior developer hungry to prove yourself, or a seasoned senior architect who has been building ML systems for years, we want to hear from you. We don't care about arbitrary years of experience&mdash;we care about your understanding of the technology, your curiosity, and your ability to execute.
 
 
 If you love keeping up with the latest AI papers, experimenting with new models, and turning research into reality, this is the place for you.
 
 
 
 
 
 What You&rsquo;ll Be Doing:
 
 
 &bull; Research &amp; Experimentation: Test, evaluate, and benchmark state-of-the-art LLMs (open-source and proprietary) to solve complex problems.
 
 
 &bull; Prototyping: Rapidly build and iterate on AI-driven prototypes and proof-of-concepts for whj.ai.
 
 
 &bull; Prompt Engineering &amp; Fine-Tuning: Optimize model outputs, design robust prompt architectures, and potentially fine-tune models for specific use cases.
 
 
 &bull; System Integration: Work alongside the broader engineering team to integrate LLM capabilities into scalable applications.
 
 
 &bull; Staying Ahead: Continuously monitor the fast-paced AI landscape to bring new techniques, tools, and methodologies into our R&amp;D pipeline.
 
 
 
 
 
 What We&rsquo;re Looking For:
 
 
 &bull; A Builder's Mindset: You are deeply curious and love tinkering with AI tools, frameworks, and APIs.
 
 
 &bull; Technical Chops: Strong programming skills, ideally in Python, with a solid grasp of software engineering fundamentals.
 
 
 &bull; LLM Knowledge: A clear understanding of how Large Language Models work, their capabilities, and their limitations (hallucinations, context limits, etc.).
 
 
 &bull; Adaptability: The ability to learn incredibly fast in a domain that changes week to week.
 
 
 &bull; Strong Communication: The ability to translate complex AI concepts into plain language for the rest of the team.
 
 
 
 
 
 Bonus Points (Nice to Have, Not Required):
 
 
 &bull; Experience with orchestration frameworks (LangChain, LlamaIndex, etc.).
 
 
 &bull; Experience working with Vector Databases (Pinecone, Weaviate, Milvus, etc.) and RAG pipelines.
 
 
 &bull; Familiarity with ML frameworks (PyTorch, TensorFlow).
 
</div>

AI Engineer - R&D

Muller's Solutions

<div>M&uuml;ller&rsquo;s Solutions is excited to announce an opening for a Google Cloud AI Specialist to drive our artificial intelligence initiatives leveraging Google Cloud Platform (GCP). In this role, you will be responsible for designing and implementing AI and machine learning solutions to help transform our data into actionable insights and enhance decision-making processes across the organization. 
Key Responsibilities:<ul><li>
Develop and deploy machine learning models using GCP tools such as AI Platform, TensorFlow, and AutoML.</li><li>
Collaborate with cross-functional teams to identify business needs and translate them into AI and ML project requirements.</li><li>
Conduct data analysis to prepare datasets for model training and evaluation while ensuring data quality and integrity.</li><li>
Implement and optimize AI workflows that facilitate real-time data processing and inference.</li><li>
Stay updated on the latest advancements in AI and machine learning technologies to continuously improve our offerings.</li><li>
Provide technical guidance and support to teams on best practices for using Google Cloud AI services.</li><li>
Document AI project implementations, model performance evaluations, and ongoing maintenance procedures.</li><li>
Contribute to developing educational materials and training sessions on AI capabilities for staff and stakeholders.</li><li>
Monitor and assess the performance of deployed AI models, making adjustments as necessary to ensure effectiveness.</li></ul> 

Requirements 
Requirements:<ul>
<li>Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.</li>
<li>3+ years of experience in machine learning or AI solutions development, preferably using Google Cloud Platform.</li>
<li>Proficient in programming languages such as Python or R, with a strong understanding of machine learning libraries (e.g., TensorFlow, scikit-learn).</li>
<li>Experience with cloud-based AI technologies, especially GCP services like Vision AI, Natural Language API, and AutoML.</li>
<li>Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.</li>
<li>Ability to work with large datasets, utilizing BigQuery or similar data processing tools.</li>
<li>Excellent problem-solving skills and a strong analytical mindset.</li>
<li>Capable of communicating complex technical concepts to diverse audiences effectively.</li>
</ul>Preferred Qualifications:<ul>
<li>Google Cloud certifications (e.g., Google Cloud Professional Data Engineer or Google Cloud Professional Machine Learning Engineer) are a plus.</li>
<li>Experience with MLOps practices and tools for model deployment and management.</li>
<li>Familiarity with DevOps practices as they relate to AI and machine learning.</li>
<li>A background in statistics or applied mathematics is desirable.</li> 
</ul> 
 
Benefits 
1- Attractive Package.
2- Family Benefits.
3- Visa.
4-Air Tickets.</div>

Google Cloud AI Specialist

TAWANTECH

<div>Job Summary: 
 
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.
Key Responsibilities:<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.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;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

<div>
 
 Job Summary:
 
 
 
 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.
 
 
 
 Key Responsibilities:
 
 
 
 <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
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <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>

<div>
 
 Why Tamara?
 
 
 
 We&rsquo;re proud to be Saudi&rsquo;s first FinTech unicorn.
 
 
 Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. &amp; There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration.
 
 
 If this sounds like you: curious, driven, and ready to build, we&rsquo;d love to meet you
 
 
 Apply now and join the next generation of Builders!
 
 
 
 About The Program
 
 
 
 At Tamara, we believe exceptional talent deserves an exceptional launchpad.
 
 
 Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn&rsquo;t a rotational &ldquo;observer&rdquo; program, it&rsquo;s a career accelerator built for those who want to build, own, and raise the bar early.
 
 
 Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You&rsquo;ll contribute immediately and grow at an accelerated pace.
 
 
 From Product to Engineering, Design to Commercial, you&rsquo;ll tackle meaningful challenges that shape how millions experience fintech across the region. You&rsquo;ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.
 
 
 Our January and June cohorts are your opportunity to move fast, think big, and start building what&rsquo;s next - not someday, but now.
 
 
 
 About The Role
 
 
 
 We&rsquo;re looking for a fresh graduate or early-career
 
 Machine Learning Engineer
 
 on a builder track.
 
 
 This role is for someone who wants to take ML from &ldquo;cool idea&rdquo; to &ldquo;running in production&rdquo;. You will work across data, modeling, and software engineering to build, deploy, and operate models that improve customer experience, reduce risk, and unlock operational efficiency.
 
 
 With the advancement of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, safety, privacy, and performance.
 
 
 
 Your Responsibilities
 
 
 
 <ul>
 <li>
 Build and ship ML systems
 </li>
 <ul>
 <li>
 Develop and deploy ML models and services that solve real business problems.
 </li>
 <li>
 Write production-quality code, tests, and documentation.
 </li>
 </ul>
 <li>
 Own the full model lifecycle
 </li>
 <ul>
 <li>
 Help with data understanding, feature creation, training, evaluation, and iteration.
 </li>
 <li>
 Set up offline and online evaluation, and monitor performance after release.
 </li>
 </ul>
 <li>
 Make ML reliable in production
 </li>
 <ul>
 <li>
 Improve model serving reliability, latency, and cost.
 </li>
 <li>
 Implement monitoring for data drift, model drift, and key quality metrics.
 </li>
 <li>
 Participate in incident response and postmortems when needed.
 </li>
 </ul>
 <li>
 Work with data and platform teams
 </li>
 <ul>
 <li>
 Partner with data engineers and platform engineers on pipelines, event-driven signals, and data quality.
 </li>
 <li>
 Use event streaming patterns when appropriate (near-real-time features, online scoring, CDC signals).
 </li>
 </ul>
 <li>
 Build tools that help others move faster
 </li>
 <ul>
 <li>
 Contribute to reusable training and serving components (templates, libraries, CI/CD, feature pipelines).
 </li>
 <li>
 Help enable safe self-serve ML and AI usage across teams.
 </li>
 </ul>
 <li>
 Use AI tools thoughtfully
 </li>
 <ul>
 <li>
 Use AI to accelerate prototyping, debugging, documentation, and test generation.
 </li>
 <li>
 Validate outputs, document assumptions, and protect sensitive data.
 
 </li>
 </ul>
 </ul>
 
 Your expertise (must have)
 
 
 
 Fresh graduate or &lt; 1 year of relevant experience (internships and projects count).
 <li>
 Solid programming fundamentals in Python (preferred) or another language used for ML systems.
 </li>
 <li>
 Strong fundamentals in:
 </li>
 <ul>
 <li>
 Data structures and algorithms (enough to write efficient, reliable code)
 </li>
 <li>
 Probability and statistics basics
 </li>
 <li>
 ML fundamentals (supervised learning, overfitting, validation, metrics)
 </li>
 </ul>
 <li>
 Comfort working with data using SQL and/or Python.
 </li>
 <li>
 A problem-solving mindset and curiosity to learn quickly.
 </li>
 <li>
 Clear communication and a collaborative approach.
 
 </li>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with common ML libraries (scikit-learn, PyTorch, TensorFlow) through coursework or projects.
 </li>
 <li>
 Familiarity with model deployment patterns (APIs, batch scoring, streaming/online scoring).
 </li>
 <li>
 Exposure to MLOps concepts (experiment tracking, model registry, CI/CD, monitoring).
 </li>
 <li>
 Familiarity with cloud (GCP/AWS) and containers (Docker) is a plus.
 </li>
 <li>
 Understanding of responsible AI and privacy (PII handling, access control, evaluation).
 </li>
 <li>
 Experience using AI assistants responsibly for coding and analysis.
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 <ul>
 <li>
 You ship at least one end-to-end ML improvement (model, feature, or service) that runs reliably.
 </li>
 <li>
 You can explain model performance clearly: what improved, what did not, and why.
 </li>
 <li>
 Monitoring is in place for your models, and you react quickly when metrics drift.
 </li>
 <li>
 You reduce manual effort for the team by adding a reusable component, template, or automation.
 </li>
 </ul>
</div>

Associate ML Engineer - Builders Program

<div><div>We help the world run better 
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div><div></div> 
What you&rsquo;ll build: 
This role is for a developer who builds AI solutions that reach production and operate reliably in enterprise environments. You will work with AI architects and data engineers within a growing AI practice. You will design and implement AI applications, agent-based workflows, and integrations across SAP landscapes, working from solution design through to deployment. 
What you bring: 
<ul><li>
3&ndash;5 years in software engineering, AI development, or equivalent experience delivering AI or data-driven solutions used in real environments.</li><li>
Experience building AI applications such as LLM-based solutions, RAG pipelines, or intelligent automation workflows. Familiarity with AI frameworks such as LangChain, LlamaIndex, or similar tools.</li><li>
Experience developing applications using languages commonly used in AI development. Python experience is strongly recommended. Experience with APIs, microservices, and containerisation is beneficial.</li><li>
Exposure to SAP BTP or similar enterprise cloud platforms is beneficial and will be developed on the job. /
Deep SAP platform knowledge is valuable but not the gating factor.</li></ul> 
What Success Looks Like<ul><li><div><ul><li>
AI applications operate reliably in production environments.</li><li>
Agent-based workflows support real business processes.</li><li>
Code and components are reusable across projects.</li><li>
Architecture transitions smoothly into implementation.</li><li>
Customers actively use the AI capabilities delivered.</li></ul></div></li></ul> 
Where you belong: 
AI Application Development (core focus):<ul><li><div><ul><li>
Build and deploy production-grade AI applications.</li><li>
Activate SAP Business AI capabilities and extend them with custom AI solutions where needed.</li><li>
Implement ML, GenAI, and RAG workflows for enterprise use cases.</li><li>
Containerise and deploy AI services using Docker or similar technologies.</li><li>
Build reusable AI components and accelerators.</li></ul></div></li></ul>
Agent-Based AI Development:<ul><li><div><ul><li>
Design and implement agent-based AI workflows.</li><li>
Implement orchestration patterns for multi-step or multi-agent scenarios, including MCP where relevant.</li><li>
Apply prompt engineering techniques to improve reliability and performance of LLM-based solutions.</li><li>
Evaluate and integrate open-source and proprietary LLMs.</li></ul></div></li></ul>
SAP Platform Integration:<ul><li><div><ul><li>
Integrate AI services with SAP BTP and SAP applications.</li><li>
Connect AI solutions with enterprise data platforms and cloud environments where required.</li></ul></div></li></ul>
Engineering and Model Lifecycle:<ul><li><div><ul><li>
Implement pipelines supporting testing, deployment, and operation of AI services.</li><li>
Contribute to monitoring, versioning, and lifecycle management of AI solutions.</li><li>
Maintain clean, maintainable code and documentation.</li></ul></div></li></ul><div> 
Bring out your best 
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
 
 
We win with inclusion 
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world. 
 
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com. 
 
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. 
 
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements. 
 
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div> 
AI Usage in the Recruitment Process</div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div>Please note that any violation of these guidelines may result in disqualification from the hiring process. 
 
Requisition ID: 448415 | Work Area: Consulting and Professional Services | Expected Travel: 0 - 90% | Career Status: Professional | Employment Type: Limited Full Time | Additional Locations: #LI-Hybrid</div>

AI Developer (One-Year Fixed Term contract)

Explore 412+ Ai engineer in Riyadh this March. Find roles across top companies and apply now to boost your career.

412 ai engineer jobs In Riyadh

Associate AI Engineer - Builders Program

AI Engineer - R&D

Google Cloud AI Specialist

Machine Learner Engineer

Machine Learner Engineer

Associate ML Engineer - Builders Program

AI Developer (One-Year Fixed Term contract)