senior data engineer

devops engineer

ai engineer

applied ai engineer

data analyst

ai data engineer

MultiBank Group

<div>
 
 Welcome to
 
 MultiBank Group
 
 , a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
 
 
 
 
 
 Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
 
 
 
 
 
 
 Role Overview:
 
 
 
 
 
 
 We are seeking an experienced
 
 AI Data Engineer
 
 to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Collaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV.
 </li>
 <li>
 Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation.
 </li>
 <li>
 Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences.
 </li>
 <li>
 Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Requirements:
 
 
 
 
 
 <ul>
 <li>
 Strong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour.
 </li>
 <li>
 Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms.
 </li>
 <li>
 Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation.
 </li>
 <li>
 Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV.
 </li>
 <li>
 Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases.
 </li>
 <li>
 Previous exposure to
 
 ETL tools
 
 (e.g., dbt, AWS Glue) and cloud environments (preferably
 
 AWS, SageMaker
 
 ).
 </li>
 <li>
 Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us?
 
 
 
 
 
 <ul>
 <li>
 Work with an industry-leading global financial institution.
 </li>
 <li>
 Competitive salary and comprehensive employee benefits.
 </li>
 <li>
 Opportunities for professional growth and career advancement.
 </li>
 <li>
 Collaborative, inclusive, and dynamic work environment.
 </li>
 <li>
 Commitment to innovation and professional excellence.
 </li>
 </ul>
 
 
 
 
 
 Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
 
 
</div>

AI Data Engineer

Parser

<div>
 
 
 Senior Data Engineer
 
 
 
 
 
 
 
 Who is Parser?
 
 
 
 Technology alone does not create impact&mdash;the right teams do. Founded in 2018, Parser is a boutique technology services and consulting firm helping global organizations solve complex business challenges through digital transformation, product development and AI enablement.
 
 
 
 
 
 We are a fast-growing team of 340+ engineers and consultants across Europe (UK, Spain, Portugal), the Americas (US, Argentina, Uruguay, Colombia), and the Middle East. We combine global reach with a mindset focused on agility, senior expertise, and close collaboration.
 
 
 We work as an extension of our clients&rsquo; teams, helping them define the right problems, shape solutions, and deliver technology-driven outcomes that create measurable business value.
 
 
 
 
 
 Our expertise spans software engineering, AI &amp; data, product development, and customer experience, delivered by teams that combine strong technical depth with a consulting mindset.
 
 
 
 
 
 
 Why Join Us?
 
 
 
 If you are looking for a place where you can think beyond execution, take true ownership of outcomes, influence decisions, and continuously learn alongside top-tier specialists in a truly global environment, we&rsquo;d love to meet you.
 
 
 
 
 
 
 How You'll Make an Impact?
 
 
 
 As a Senior Data Engineer you will be participating in the design and build of the next generation of AI-driven data products and intelligence platforms. As a Python-strong, AI-aware Data Engineer, you'll lead the design and development of data ingestion, ETL, and multi-agent analytical systems by creating scalable schemas and transformation layers that power analytics and AI agents across the UAE and beyond.
 
 
 
 
 
 
 Your key responsibilities:
 
 
 <ul>
 <li>
 Build and maintain end-to-end
 
 data ingestion and ETL pipelines
 
 </li>
 <li>
 Ingest structured and unstructured data from APIs, Snowflake, Oracle, documents, and market data providers
 </li>
 <li>
 Develop production-quality Python services and data workflows
 </li>
 <li>
 Orchestrate pipelines using Kubernetes and workflow tools
 </li>
 <li>
 Apply clean architecture and strong engineering design patterns
 </li>
 <li>
 Design schemas and transformation layers for analytics and AI agents
 </li>
 <li>
 Prepare data for
 
 AI and RAG systems
 
 (chunking, embeddings, retrieval pipelines)
 </li>
 </ul>
 
 
 
 
 
 What you&rsquo;ll bring to the role:
 
 
 
 
 
 
 
 Essential Requirements:
 
 
 <ul>
 <li>
 6+ years of experience in Python
 </li>
 <li>
 3+ years of experience with Kubernetes-based workloads
 </li>
 <li>
 ETL/ELT pipeline Design and orchestration (Airflow, ADF, Databricks or similar)
 </li>
 <li>
 Hands on experience with RAG systems, Embeddings and Vector Databases.
 </li>
 <li>
 Experience with Azure cloud
 </li>
 <li>
 Experience with Data Warehouse Architectures, API and Database integrations
 </li>
 </ul>
 
 
 
 
 
 Desirable Requirements:
 
 
 <ul>
 <li>
 Experience with Snowflake and Oracle
 </li>
 <li>
 Kafka/Event hub streaming systems
 </li>
 <li>
 LLM evaluation, prompt engineering
 </li>
 <li>
 Experience building AI or Data Platforms.
 </li>
 </ul>
 
 
 
 
 
 Location:
 
 
 
 Only considering candidates based in
 
 Dubai or Abu Dhabi.
 
 
 
 Hybrid work model
 
 2-3 days
 
 at the office per week.
 
 
 
 
 
 
 You will receive:
 
 
 <ul>
 <li>
 The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
 </li>
 <li>
 The opportunity to be part of an amazing, multicultural community of tech experts.
 </li>
 <li>
 A highly competitive compensation package.
 </li>
 <li>
 A flexible and hybrid working environment.
 </li>
 <li>
 Employment Visa and Medical insurance.
 </li>
 </ul>
 
 
 
 
 Parser is committed to fostering an inclusive workplace and providing equal employment opportunities to all applicants regardless of race, religion, gender, sexual orientation, age, disability, or any other protected characteristic under applicable law.
 
 
 
 
 
 If you require reasonable accommodations during the recruitment process, please let us know and we will work with you to support your participation.
 
 
 
 
 
 By applying to this role, you acknowledge that your personal data will be processed in accordance with Parser&rsquo;s Privacy Notice for recruitment purposes.
 
 
 
 
 
 Parser may use AI-assisted tools during certain stages of the recruitment process to support operational efficiency. Our recruiting teams use AI to streamline note-taking and scheduling. All hiring decisions are made by people, with human review and oversight.
 
 
 
 
 
 Come and join our #ParserCommunity.
 
 
 https://parserdigital.com/
 
 
 Follow us on
 
 Linkedin
 
 
 
 
 
</div>

Senior Data Engineer

Ministry of Economy & Tourism

<div>
 
 
 الهدف العام للوظيفة
 
 
 
 خبير في الذكاء الاصطناعي ضمن قسم الذكاء الاصطناعي في الوزارة، يتولى ضمان نشر أنظمة الذكاء الاصطناعي بصورة فعّالة وأخلاقية وقابلة للتوسع عبر عمليات الوزارة. يجسّر هذا الدور الفجوة بين القدرات التقنية للذكاء الاصطناعي والاحتياجات المؤسسية الحيوية، من خلال الإشراف البشري المتمحور حول الإنسان وحوكمة الأنظمة وتحسينها المستمر. يجمع هذا المنصب بين العمق التقني ومعرفة الأعمال وإدارة أصحاب المصلحة وقيادة التغيير لضمان استدامة تطبيقات الذكاء الاصطناعي وتحقيقها لقيمة مؤسسية قابلة للقياس
 
 
 
 المسؤوليات الرئيسية
 
 
 <ul>
 <li>
 تحديد متطلبات البيانات الجاهزة للذكاء الاصطناعي والإشراف عليها بما يشمل بيانات التدريب وبيانات الإدخال التشغيلية ونماذج القرار، وضمان جودتها واتساقها.
 </li>
 <li>
 تصميم وإدارة سير عمل الإشراف البشري-الآلي (Human-in-the-Loop) للتحقق من مخرجات الذكاء الاصطناعي قبل النشر التشغيلي.
 </li>
 <li>
 مراقبة دقة نماذج الذكاء الاصطناعي ومستويات الثقة والكشف عن انحراف الأداء للحفاظ على الفاعلية التشغيلية وضمان الاستمرارية.
 </li>
 <li>
 اختبار وكلاء الذكاء الاصطناعي وتدريبهم من خلال آليات التغذية الراجعة وهندسة الطلبات وبروتوكولات التعلم الخاضع للإشراف.
 </li>
 <li>
 تطوير وتطبيق أطر حوكمة الذكاء الاصطناعي والمبادئ التوجيهية الأخلاقية وسياسات الامتثال المتوافقة مع اللوائح الحكومية المعتمدة.
 </li>
 <li>
 المشاركة في تصنيف تطبيقات الذكاء الاصطناعي حسب مستوى مخاطرها وتأثيرها، وإرساء معايير رقابة متدرجة تتناسب مع درجة خطورة كل تطبيق.
 </li>
 <li>
 قيادة الإشراف على الموردين وحوكمة العقود لضمان السلطة التقنية والشفافية ومنع الاحتكار التقني من قِبل الموردين.
 </li>
 <li>
 تحديد مخاطر الذكاء الاصطناعي والتخفيف منها بما تشمل عدم موضوعية النموذج في نتائجه، ومحاولات التلاعب بالنموذج، وإفساد بيانات التدريب، وتراجع أداء النماذج بمرور الوقت.
 </li>
 <li>
 تصميم وقيادة برامج التثقيف في الذكاء الاصطناعي للمطورين والمستخدمين وأصحاب المصلحة المتأثرين بتطبيقات الذكاء الاصطناعي عبر الوزارة.
 </li>
 <li>
 إرشاد فرق العمل المشتركة وتنسيق التعاون متعدد التخصصات بين فرق تطوير الحلول والهندسة والتشغيل والأعمال.
 </li>
 <li>
 ترجمة القدرات والقيود التقنية لأنظمة الذكاء الاصطناعي إلى توصيات عملية وتوجيهات واضحة تُمكّن الإدارة وأصحاب المصلحة من اتخاذ قرارات مدروسة.
 </li>
 <li>
 تحديد مؤشرات أداء نماذج الذكاء الاصطناعي ومتابعتها بما تشمل نسبة الدقة، ودرجة يقين النموذج، ومعدلات قبول المخرجات، ومؤشرات انحراف الأداء، وإعداد التقارير الدورية.
 </li>
 <li>
 إدارة حلقات التغذية الراجعة من مستخدمي الذكاء الاصطناعي والفرق التشغيلية لتحسين النماذج والعمليات باستمرار.
 </li>
 <li>
 تحديد حالات استخدام الذكاء الاصطناعي الناشئة والتوصية بتحسينات على سير العمل والواجهات لتحقيق أقصى قيمة مؤسسية.
 </li>
 <li>
 دعم التوسع في نشر تطبيقات الذكاء الاصطناعي عبر الوزارة من خلال توحيد المعايير، وبناء قوالب وأدوات جاهزة قابلة لإعادة الاستخدام، وتوثيق أفضل الممارسات لضمان الاتساق والكفاءة.
 </li>
 <li>
 التعامل مع عزوف الموظفين وترددهم في تبني الذكاء الاصطناعي من خلال ربط تطبيقاته بواقع عمل كل فريق، وبناء الثقة، وتعزيز الانفتاح لتسريع تبني الحلول الذكية.
 </li>
 <li>
 بناء شبكات تبادل المعرفة والخبرات في مجال الذكاء الاصطناعي عبر الجهات الحكومية، وتعزيز التعاون ومشاركة أفضل الممارسات بين الكوادر المتخصصة.
 </li>
 <li>
 التحقق من مخرجات نماذج الذكاء الاصطناعي وتحديد الحالات الحدية والاستثنائية، وتطبيق الحكم البشري المدروس في القرارات المعقدة لضمان موثوقية الأنظمة ودقتها.
 </li>
 <li>
 تنفيذ أي مهام أخرى يكلف بها رئيس القسم في نطاق اختصاصه.
 </li>
 </ul>
 
 
 المؤهلات والخبرة
 
 
 <ul>
 <li>
 دكتوراه - علوم الحاسب / الذكاء الاصطناعي / هندسة / إحصاء أو ما يعادلها (بدون خبرة)
 </li>
 <li>
 ماجستير - علوم الحاسب / الذكاء الاصطناعي / علوم البيانات / هندسة أو ما يعادلها (3 سنوات خبرة)
 </li>
 <li>
 بكالوريوس - علوم الحاسب / الذكاء الاصطناعي / هندسة الحاسوب / إحصاء أو ما يعادلها (7 سنوات خبرة)
 </li>
 </ul>
 
 
 الشهادات المهنية
 
 
 <ul>
 <li>
 شهادة معتمدة في الذكاء الاصطناعي وتعلم الآلة على المنصات السحابية مثل Google Cloud Professional ML Engineer / AWS Machine Learning Specialty / Microsoft Azure AI Engineer Associate
 </li>
 <li>
 شهادة في نماذج اللغة الكبيرة وهندسة الطلبات مثل DeepLearning.AI Generative AI / Prompt Engineering Specialization
 </li>
 <li>
 شهادة في حوكمة الذكاء الاصطناعي وأخلاقياته مثل IAPP AI Governance Professional / ISO 42001 Lead Implementer)
 </li>
 <li>
 شهادة في علوم البيانات وهندستها مثل IBM Data Science Professional / Databricks Data Engineer Associate)
 </li>
 <li>
 شهادة في تشغيل نماذج الذكاء الاصطناعي مثل MLflow MLOps Certified / Kubeflow Practitioner / DataRobot MLOps
 </li>
 <li>
 شهادة في أمن الذكاء الاصطناعي والهجمات المعادية مثل Certified AI Security Professional / OWASP AI Security
 </li>
 <li>
 شهادة في إدارة المشاريع وقيادة التغيير أو ما يعادلها PMP / PRINCE2 / Prosci Change Management
 </li>
 <li>
 دورة في تصميم سير العمل الإنساني-الآلي (Human-in-the-Loop) واختبار النماذج وتقييم الانجراف
 </li>
 <li>
 دورة في بنية بيانات الذكاء الاصطناعي ورسم خرائط المعرفة (Knowledge Graphs / Data Mapping)
 </li>
 <li>
 دورة في قياس أداء نماذج الذكاء الاصطناعي ومؤشرات الدقة ومعدلات القبول
 </li>
 <li>
 دورة في أساسيات أمن المعلومات وحماية البيانات في بيئات الذكاء الاصطناعي الحكومية
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Job Purpose
 
 
 
 Serve as an Artificial Intelligence (AI) expert within the Ministry's AI Department, responsible for ensuring the effective, ethical, and scalable deployment of AI systems across the Ministry's operations. This role bridges the gap between AI technical capabilities and critical business needs through human-centered oversight, AI governance, and continuous optimization. The position combines deep technical expertise with business knowledge, stakeholder management, and change leadership to ensure AI applications remain sustainable and deliver measurable organizational value.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Define and oversee AI-ready data requirements, including training datasets, operational input data, and decision models, while ensuring data quality, consistency, and integrity.
 </li>
 <li>
 Design and manage Human-in-the-Loop (HITL) workflows to validate AI outputs before operational deployment.
 </li>
 <li>
 Monitor AI model accuracy, confidence levels, and performance drift to maintain operational effectiveness and ensure service continuity.
 </li>
 <li>
 Test and train AI agents using feedback mechanisms, prompt engineering, and supervised learning protocols.
 </li>
 <li>
 Develop and implement AI governance frameworks, ethical guidelines, and compliance policies aligned with approved government regulations.
 </li>
 <li>
 Participate in classifying AI applications according to their risk and impact levels and establish proportionate control measures based on the level of risk.
 </li>
 <li>
 Lead vendor oversight and contract governance to ensure technical ownership, transparency, and prevent vendor lock-in.
 </li>
 <li>
 Identify and mitigate AI-related risks, including model bias, adversarial attacks, training data poisoning, and model performance degradation over time.
 </li>
 <li>
 Design and lead AI awareness and education programs for developers, end users, and stakeholders affected by AI implementations across the Ministry.
 </li>
 <li>
 Guide cross-functional teams and coordinate multidisciplinary collaboration among solution development, engineering, operations, and business teams.
 </li>
 <li>
 Translate the technical capabilities and limitations of AI systems into practical recommendations and clear guidance to support informed decision-making by management and stakeholders.
 </li>
 <li>
 Define and monitor AI model performance metrics, including accuracy rates, confidence scores, output acceptance rates, and model drift indicators, and prepare periodic performance reports.
 </li>
 <li>
 Manage feedback loops from AI users and operational teams to continuously improve AI models and business processes.
 </li>
 <li>
 Identify emerging AI use cases and recommend workflow and user interface enhancements to maximize organizational value.
 </li>
 <li>
 Support the enterprise-wide scaling of AI applications by standardizing practices, developing reusable templates and tools, and documenting best practices to ensure consistency and efficiency.
 </li>
 <li>
 Address employee resistance and hesitation toward AI adoption by aligning AI solutions with team-specific business needs, building trust, and promoting openness to accelerate the adoption of intelligent solutions.
 </li>
 <li>
 Build knowledge-sharing networks and AI communities of practice across government entities, fostering collaboration and the exchange of best practices among AI professionals.
 </li>
 <li>
 Validate AI model outputs, identify edge cases and exceptional scenarios, and apply sound human judgment in complex decision-making to ensure the reliability and accuracy of AI systems.
 </li>
 <li>
 Perform any other duties assigned by the Head of the AI Department within the scope of the role.
 </li>
 </ul>
 
 
 Qualifications &amp; Experience
 
 
 <ul>
 <li>
 PhD in Computer Science, Artificial Intelligence, Engineering, Statistics, or a related field (no experience required).
 </li>
 <li>
 Master's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (minimum 3 years of relevant experience).
 </li>
 <li>
 Bachelor's Degree in Computer Science, Artificial Intelligence, Computer Engineering, Statistics, or a related field (minimum 7 years of relevant experience).
 </li>
 </ul>
 
 
 Professional Certifications
 
 
 <ul>
 <li>
 Professional certification in Artificial Intelligence and Machine Learning on cloud platforms, such as
 
 Google Cloud Professional Machine Learning Engineer
 
 ,
 
 AWS Machine Learning Specialty
 
 , or
 
 Microsoft Azure AI Engineer Associate
 
 .
 </li>
 <li>
 Certification in Large Language Models (LLMs) and Prompt Engineering, such as
 
 DeepLearning.AI Generative AI Specialization
 
 or
 
 Prompt Engineering Specialization
 
 .
 </li>
 <li>
 Certification in AI Governance and Ethics, such as
 
 IAPP AI Governance Professional (AIGP)
 
 or
 
 ISO/IEC 42001 Lead Implementer
 
 .
 </li>
 <li>
 Certification in Data Science and Data Engineering, such as
 
 IBM Data Science Professional Certificate
 
 or
 
 Databricks Data Engineer Associate
 
 .
 </li>
 <li>
 Certification in AI Operations (MLOps), such as
 
 MLflow MLOps Certified
 
 ,
 
 Kubeflow Practitioner
 
 , or
 
 DataRobot MLOps
 
 .
 </li>
 <li>
 Certification in AI Security and Adversarial AI, such as
 
 Certified AI Security Professional
 
 or
 
 OWASP AI Security
 
 .
 </li>
 <li>
 Certification in Project Management and Change Leadership, such as
 
 PMP
 
 ,
 
 PRINCE2
 
 , or
 
 Prosci Change Management
 
 .
 </li>
 <li>
 Training course in
 
 Human-in-the-Loop (HITL)
 
 workflow design, AI model testing, and model drift evaluation.
 </li>
 <li>
 Training course in AI data architecture, data mapping, and knowledge graphs.
 </li>
 <li>
 Training course in AI model performance measurement, including accuracy metrics, confidence scores, and output acceptance rates.
 </li>
 <li>
 Training course in information security fundamentals and data protection in government AI environments.
 </li>
 </ul>
 
 
 
</div>

خبير الذكاء الاصطناعي - Artificial Intelligence Expert

Fuse Energy

<div>Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more. 
 
We&rsquo;re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers. 
 
But we&rsquo;re not stopping there. We&rsquo;re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries. 
 
We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse. 
 
Responsibilities<ul><li>
Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)</li><li>
Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows</li><li>
Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms</li><li>
Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing</li><li>
Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts</li><li>
Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space</li>
Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively 
<li>
</li></ul> 
 
Requirements 
<ul><li>
Minimum 3 years of engineering experience</li><li>
Proven experience as a Backend Engineer with a strong interest and practical experience in applied AI or machine learning</li><li>
Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)</li><li>
Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production</li><li>
Solid understanding of cloud technologies, containerisation and building scalable AI applications</li><li>
Ability to integrate AI/ML models into real-world applications, focusing on usability and performance</li><li>
Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment</li><li>
Experience working with large datasets, particularly in relation to demand and supply forecasting</li></ul>
Bonus<ul><li>
Experience or strong interest in energy markets and trading strategies</li><li>
Understanding of weather forecasting, energy demand patterns, and production modelling</li><li>
Exposure to Natural Language Processing (NLP) or other related fields</li></ul> 

Benefits 
<ul><li>
Competitive salary and an equity sign-on bonus</li><li>
Biannual bonus scheme</li><li>
Fully expensed tech to match your needs</li><li>
Paid annual leave</li><li>
Breakfast and dinner allowance for office based employees</li></ul></div>

Applied AI Engineer

Snowflake

<div>
 At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don&rsquo;t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset &mdash; who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
 
 
 
 Solution Engineer (South Africa): Accelerate the AI Data Cloud
 
 
 
 We are looking for a
 
 Solution Engineer
 
 who is accustomed to solving customer&rsquo;s most complex problems and closing large deals. In this role you will work directly with the accounts sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. As a Snowflake Solution Engineer you must share our passion about driving the
 
 AI Data Cloud
 
 adoption, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences and bridging the gap between audiences when needed.
 
 
 
 YOUR IMPACT (IN THIS ROLE YOU WILL GET TO):
 
 
 
 <ul>
 <li>
 Present Snowflake technology and vision, focusing on the AI Data Cloud and its capabilities, to executives and technical contributors at prospects and customers.
 </li>
 <li>
 Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation.
 </li>
 <li>
 Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them.
 </li>
 <li>
 Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake&rsquo;s products and marketing.
 
 
 
 </li>
 </ul>
 
 YOUR CREDENTIALS (ON DAY ONE, WE WILL EXPECT YOU TO HAVE):
 
 
 
 <ul>
 <li>
 3-8+ years of industry pre-sales experience.
 </li>
 <li>
 Outstanding presenting skills and executive presence to engage technical, business and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
 </li>
 <li>
 Strong understanding and practical experience with value-based selling and sales methodologies / frameworks (e.g., MEDDPIC/MEDDIC) to drive complex deals.
 </li>
 <li>
 Broad range of experience within Data platforms, analytics, and cloud technologies, including deep knowledge of data warehousing, data lakes, and lake house architectures.
 </li>
 <li>
 Proven ability to discuss and demonstrate the value of Generative AI and Machine Learning (ML) use cases for enterprises.
 </li>
 <li>
 Familiarity with core data concepts such as data modeling, data governance, and data engineering best practices.
 </li>
 <li>
 Deep hands-on expertise with Python and SQL.
 </li>
 <li>
 University degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred.
 </li>
 <li>
 Experience in the UAE market with preference already being based there.
 </li>
 <li>
 Arabic fluency is highly desirable / nice to have.
 
 
 
 </li>
 </ul>
 
 OUR VALUES. OUR CULTURE.
 
 
 
 We are customer-obsessed. We lead with integrity and honesty. We believe in being great teammates, embracing feedback, and embodying the
 
 Snowflake values
 
 in every interaction. We work to ensure data is accessible, usable, and valuable to everyone.
 
 
 
 If this sounds like the high-stakes, high-reward role you were made for, seize the moment. Apply now and join us in building the AI Data Cloud for the region!
 
 
 
 Snowflake is growing fast, and we&rsquo;re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
 
 
 How do you want to make your impact?
 
 
 For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
</div>

Solution Engineer - South Africa

Jorofy Private Limited

We are seeking a highly skilled Senior AI Engineer (PhD) to lead the design, development, and deployment of advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess a PhD in Artificial Intelligence, Machine Learning, Computer Science, Data Science, or a related field, along with extensive industry experience in developing AI-driven products, conducting research, and translating innovative concepts into scalable enterprise solutions.The role requires expertise in Generative AI, Large Language Models (LLMs), Deep Learning, Natural Language Processing (NLP), Computer Vision, and MLOps practices.Key ResponsibilitiesAI Research &amp; Innovation<ul><li>Conduct advanced research in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.</li><li>Evaluate emerging AI technologies, frameworks, and methodologies to enhance organizational capabilities.</li><li>Publish research findings, technical papers, patents, or contribute to industry thought leadership initiatives.</li><li>Lead proof-of-concept (PoC) development for innovative AI solutions.</li></ul>Solution Design &amp; Development<ul><li>Architect and develop scalable AI/ML models and intelligent systems.</li><li>Design and optimize Large Language Model (LLM)-based applications and AI agents.</li><li>Build and fine-tune machine learning and deep learning models for production environments.</li><li>Develop AI-powered applications involving NLP, Computer Vision, Predictive Analytics, and Recommendation Systems.</li><li>Integrate AI solutions with enterprise platforms, APIs, and cloud environments.</li></ul>Generative AI &amp; LLM Engineering<ul><li>Develop and optimize Retrieval-Augmented Generation (RAG) architectures.</li><li>Fine-tune foundation models and implement prompt engineering strategies.</li><li>Design AI agents, autonomous workflows, and conversational AI solutions.</li><li>Implement vector databases and semantic search frameworks.</li><li>Evaluate model performance, accuracy, safety, and responsible AI practices.</li></ul>MLOps &amp; Deployment<ul><li>Build end-to-end ML pipelines for model training, deployment, monitoring, and maintenance.</li><li>Implement CI/CD processes for AI applications.</li><li>Optimize model performance, scalability, and infrastructure costs.</li><li>Monitor model drift and ensure continuous improvement.</li></ul>Leadership &amp; Collaboration<ul><li>Provide technical leadership and mentorship to AI Engineers, Data Scientists, and ML Engineers.</li><li>Collaborate with business stakeholders to identify AI opportunities and define solution roadmaps.</li><li>Participate in strategic technology planning and AI transformation initiatives.</li><li>Review code, architecture, and technical deliverables to ensure quality standards.</li></ul>Required QualificationsEducation<ul><li>PhD in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Statistics, or a related discipline.</li></ul>Experience<ul><li>8+ years of experience in AI/ML development, including research and production deployment.</li><li>Proven experience leading AI projects in enterprise environments.</li><li>Experience working with Generative AI, LLMs, and advanced deep learning architectures.</li></ul>Technical SkillsProgramming<ul><li>Python (Advanced)</li><li>SQL</li><li>Java, C++, or Scala (Preferred)</li></ul>AI/ML Frameworks<ul><li>PyTorch</li><li>TensorFlow</li><li>Keras</li><li>Scikit-learn</li><li>Hugging Face Transformers</li></ul>Generative AI &amp; LLM Technologies<ul><li>OpenAI APIs</li><li>LangChain</li><li>LangGraph</li><li>LlamaIndex</li><li>RAG Architectures</li><li>Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)</li></ul>Cloud Platforms<ul><li>AWS</li><li>Microsoft Azure</li><li>Google Cloud Platform (GCP)</li></ul>MLOps &amp; DevOps<ul><li>Docker</li><li>Kubernetes</li><li>MLflow</li><li>Kubeflow</li><li>Jenkins</li><li>GitHub Actions</li></ul>Databases<ul><li>PostgreSQL</li><li>MongoDB</li><li>Vector Databases</li></ul>Preferred Qualifications<ul><li>Publications in reputed journals or AI conferences (NeurIPS, ICML, ICLR, ACL, CVPR, etc.).</li><li>Experience in Agentic AI, Autonomous Systems, and Multi-Agent Frameworks.</li><li>Knowledge of AI Governance, Responsible AI, Explainable AI (XAI), and AI Security.</li><li>Industry certifications in Cloud, AI, or Machine Learning technologies.</li></ul>Core Competencies<ul><li>Strategic Thinking</li><li>Research &amp; Innovation</li><li>Problem Solving</li><li>Leadership &amp; Team Mentoring</li><li>Stakeholder Management</li><li>Communication &amp; Presentation Skills</li><li>Analytical Thinking</li><li>Project Management</li></ul>Key Deliverables<ul><li>Production-ready AI and Generative AI solutions.</li><li>Scalable machine learning pipelines and architectures.</li><li>AI research initiatives and innovation roadmaps.</li><li>Performance optimization and continuous model improvement.</li><li>Technical mentorship and knowledge-sharing across teams.</li></ul>Experience Required: 8&ndash;15+ Years Education: PhD (Mandatory) Level: Senior / Lead Individual Contributor or Technical Lead Role.Education:<ul><li>Master's (Preferred)</li></ul>Experience:<ul><li>Senior Engineer: 10 years (Required)</li></ul>Work Location: In person

Senior AI Engineer (PhD)

Raw Ventures

<div>
 
 We build AI-powered products internally and support portfolio companies with complex data and AI infrastructure challenges. We are looking for an engineer who enjoys building the foundation beneath AI systems: data pipelines, backend services, storage architecture, APIs and the infrastructure that turns messy real-world data into usable products.
 
 
 This is a hands-on role with significant ownership and direct exposure to founders, operators, and investors.
 
 
 
 
 
 
 The role
 
 
 
 You will own the data and backend layer behind AI products and internal platforms.
 
 
 This is not a pure ML role. We need someone who enjoys designing databases, building ingestion systems, operating data infrastructure, and shipping production services. AI sits on top of that foundation.
 
 
 
 
 
 
 Stack
 
 
 
 Python &bull; PostgreSQL &bull; ClickHouse &bull; Airflow / Dagster &bull; dbt &bull; AWS / GCP &bull; Docker &bull; Kubernetes &bull; OpenAI &bull; Anthropic &bull; Vector Databases
 
 
 
 
 
 
 What you'll do
 
 
 <ul>
 <li>
 Design and build data lakes, warehouses, and backend systems
 </li>
 <li>
 Build data ingestion services, APIs, ETL/ELT pipelines, and workflow orchestration
 </li>
 <li>
 Design relational and analytical databases (Postgres, ClickHouse, BigQuery, DuckDB or similar)
 </li>
 <li>
 Build infrastructure for LLM applications, RAG systems, embeddings, and retrieval pipelines
 </li>
 <li>
 Deploy and operate production systems using Docker, Kubernetes, CI/CD, and cloud infrastructure
 </li>
 <li>
 Work directly with founders and product teams on data-intensive and AI-driven products
 </li>
 </ul>
 
 
 
 
 
 What we expect
 
 
 <ul>
 <li>
 5+ years building production backend systems
 </li>
 <li>
 Strong Python
 </li>
 <li>
 Strong database design and data modelling experience
 </li>
 <li>
 Experience building and operating data pipelines at scale
 </li>
 <li>
 Experience with modern data tooling (Airflow, Dagster, dbt, Kafka, Spark, etc.)
 </li>
 <li>
 Practical experience with LLM systems, RAG, vector databases, or AI infrastructure
 </li>
 <li>
 Cloud infrastructure experience (AWS, GCP, or Azure)
 </li>
 <li>
 Russian fluent or native (required)
 </li>
 </ul>
 
 
 
 
 
 Nice to have
 
 
 
 Go &bull; TypeScript &bull; ClickHouse &bull; BigQuery &bull; DuckDB &bull; Kafka &bull; Spark &bull; ML frameworks &bull; Forecasting &bull; Recommendation Systems &bull; Time-Series Data &bull; Geospatial Data &bull; Startup Experience
 
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Fully remote
 </li>
 <li>
 Direct access to founders and investors
 </li>
 <li>
 Work across multiple AI products and companies
 </li>
 <li>
 High ownership and autonomy
 </li>
 <li>
 Exposure to both engineering and venture investing
 </li>
 <li>
 Competitive compensation, discussed individually
 </li>
 </ul>
 
 
 
</div>

Backend & Data Engineer

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