ai automation llms rag engineer

Sadat Consulting

Sen your CV across mohammed.sadatgac@gmail.com with below details1. Notice period 2. Current salary 3. Expected salary 4. Do you have Transferable IQAMARole Purpose Develop AI-enabled automation aligned with roadmap including automation workflows, AIassisted reporting, anomaly detection, and enterprise AI integration patterns.Key Responsibilities<ul><li>Develop automation pipelines and workflow automations</li><li>Integrate enterprise AI services (LLM APIs, automation endpoints)</li><li>Develop anomaly detection logic and operational intelligence rules</li><li>Build AI-assisted reporting components aligned with dashboards</li><li>Maintain AI/automation documentation and reproducibility</li><li>Ensure governance-aligned AI implementation (approval where required)</li><li>Support integration of AI outputs into enterprise apps (Frappe, dashboards)</li></ul>Mandatory Technical Requirements<ul><li>Python (ML/automation stack)</li><li>Experience integrating enterprise AI APIs</li><li>Familiarity with RAG architecture concepts</li><li>Automation frameworks and scripting (job scheduling, pipelines)</li><li>Strong integration skills (API-based orchestration)</li></ul>Minimum Experience<ul><li>8+ years experience</li><li>Proven delivery of AI/automation in enterprise environments</li></ul>Job Types: Full-time, PermanentWork Location: In person

AI Automation (LLMs, RAG) Engineer

TAWANTECH

<div>Job Summary
We are seeking an AI Software Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies to develop intelligent solutions that enhance customer experience, operational efficiency, and knowledge management within the banking sector.
Key Responsibilities<ul><li>Design, develop, and deploy AI-powered applications leveraging LLMs and Generative AI.</li><li>Build Retrieval-Augmented Generation (RAG) solutions using enterprise banking data.</li><li>Develop intelligent assistants, chatbots, and knowledge management solutions.</li><li>Integrate AI services with banking applications and APIs.</li><li>Fine-tune, evaluate, and optimize LLM performance.</li><li>Ensure compliance with banking security, governance, and regulatory requirements.</li><li>Collaborate with business, data, and technology teams to deliver AI-driven solutions.</li></ul> 
Requirements<ul><li> 
4+ years of software engineering experience.</li><li>Strong Python programming skills.</li><li>Experience with LLMs, Generative AI, and Prompt Engineering.</li><li>Experience with LangChain, LlamaIndex, Vector Databases, and RAG architectures.</li><li>Familiarity with machine learning frameworks and AI deployment practices.</li><li>Experience with cloud platforms (AWS, Azure, GCP) is preferred.</li></ul>
Preferred Qualifications<ul><li>Banking or Financial Services experience.</li><li>Experience developing AI copilots or customer-facing AI solutions.</li><li>Knowledge of AI governance and responsible AI practices.</li></ul></div>

AI Software Engineer / LLM Engineer

DeepSource Technologies

<div>We are looking for a highly capable Senior AI Engineer / MLOps Engineer to join our team and lead the design, development, deployment, and optimization of scalable, production-grade AI and machine learning solutions. The ideal candidate will have strong hands-on experience across AI engineering, machine learning, MLOps, cloud-native architecture, and data engineering, with the ability to transform experimentation into reliable, business-ready systems.
This role requires deep expertise in LLMs, RAG, agentic AI workflows, CI/CD automation, production ML lifecycle management, and modern data platforms. The selected candidate will be expected to lead end-to-end AI initiatives, work across multiple projects, collaborate with technical and business stakeholders, and ensure operational excellence across AI platforms.
Key Responsibilities<ul><li>Design, develop, deploy, and maintain production-grade AI and machine learning systems end to end.</li><li>Build and optimize LLM-powered applications, including RAG pipelines, prompt workflows, agent-based systems, and multimodal AI use cases.</li><li>Develop intelligent workflows using tool-calling, orchestration frameworks, and contextual reasoning patterns.</li><li>Fine-tune, evaluate, and operationalize machine learning and foundation models for enterprise use cases.</li><li>Build and manage MLOps pipelines covering training, evaluation, model registration, deployment, monitoring, and retraining.</li><li>Implement CI/CD pipelines for ML and AI workflows to support automated testing, release management, and controlled deployments.</li><li>Establish model monitoring frameworks for drift detection, feature attribution, inference quality, and performance tracking.</li><li>Ensure reproducibility, reliability, and version control across AI/ML environments.</li><li>Architect scalable AI/ML platforms using modern compute, storage, orchestration, monitoring, and search services.</li><li>Build repeatable environments using Infrastructure as Code.</li><li>Support secure, high-availability, and cost-efficient deployment models across development, staging, and production environments.</li><li>Design scalable inference and serving patterns for variable workloads.</li><li>Build and maintain automated data pipelines, ETL/ELT workflows, and data processing frameworks for AI/ML consumption.</li><li>Ensure data quality, lineage, governance, and versioning to support dependable model training and inference.</li><li>Work with structured and unstructured datasets across data lakes, data warehouses, and operational systems.</li><li>Deliver analytics-ready datasets to downstream systems and applications.</li><li>Lead multiple AI initiatives in parallel, including planning, execution, and coordination with internal teams and stakeholders.</li><li>Work closely with product, engineering, data, and business teams to deliver production-ready AI capabilities.</li><li>Contribute to architecture decisions, technical documentation, best practices, and engineering standards.</li><li>Support knowledge sharing, technical leadership, and continuous improvement across the AI function. 
</li></ul> 
 
Requirements<ul><li> 
Bachelor&rsquo;s degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>5+ years of hands-on experience in AI engineering, machine learning engineering, MLOps, or data/ML platform engineering.</li><li>Proven experience deploying production AI/ML solutions in enterprise environments.</li><li>Strong programming experience in Python and SQL.</li><li>Strong experience with enterprise AI/ML architecture and delivery.</li></ul></div>

AI Architect - Riyadh,KSA

aramco digital

<div>
 
 
 Overview:
 
 
 
 The Sr. AI &amp; Data Expert is a highly skilled individual contributor responsible for designing and implementing advanced AI systems and scalable data platforms. This role focuses on building next generation AI solutions&mdash;including agentic AI systems, LLM-based applications, and industrial data pipelines&mdash;that transform data into actionable business outcomes. The position requires deep expertise across AI/ML, data engineering, and cloud platforms, along with the ability to translate business needs into technically robust and production-ready solutions.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design and implement agentic AI systems, including multi-agent frameworks and autonomous workflows
 </li>
 <li>
 Develop and optimize RAG pipelines, LLM integrations, and model fine-tuning for real-world applications
 </li>
 <li>
 Build production-grade AI services and APIs, ensuring scalability, performance, and reliability
 </li>
 <li>
 Design and implement scalable data architectures for structured and unstructured data
 </li>
 <li>
 Build and maintain data pipelines supporting ingestion, processing, and consumption layers
 </li>
 <li>
 Ensure data quality, consistency, and availability across AI and analytics workloads
 </li>
 <li>
 Troubleshoot and resolve complex technical challenges across AI, data, and platform layers
 </li>
 <li>
 Optimize systems for performance, latency, and cost efficiency, especially in high-scale environments
 </li>
 <li>
 Contribute to reusable components, frameworks, and engineering best practices
 </li>
 <li>
 Implement and maintain end-to-end ML/LLM lifecycle workflows, including training, deployment, and monitoring
 </li>
 <li>
 Integrate CI/CD pipelines for AI systems and automate model validation, testing, and releases
 </li>
 <li>
 Monitor model performance, drift, and system health in production
 </li>
 <li>
 Design and deploy AI/data solutions across multi-cloud or hybrid environments, including GPU-based workloads
 </li>
 <li>
 Work with modern infrastructure stacks to support scalable AI processing and storage
 </li>
 <li>
 Ensure efficient utilization of compute resources and cloud services
 </li>
 <li>
 Apply data governance, security, and compliance standards, including data sovereignty requirements
 </li>
 <li>
 Implement Responsible AI practices, ensuring transparency, fairness, and secure model usage
 </li>
 <li>
 Contribute to defining guardrails for safe and compliant AI deployment
 </li>
 <li>
 Translate business requirements into AI and data solutions aligned with KPIs and measurable outcomes
 </li>
 <li>
 Collaborate with product, engineering, and business teams to deliver end-to-end solutions
 </li>
 <li>
 Provide technical input to support decision-making and solution design
 </li>
 <li>
 Contribute to documentation, standards, and reusable assets.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 
 
 Education:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Master&rsquo;s degree is a plus.
 </li>
 </ul>
 
 
 
 
 
 Experience:
 
 
 <ul>
 <li>
 10&ndash;14 years of experience in AI/ML, data engineering, or related domains
 </li>
 <li>
 Strong hands-on experience building and deploying AI/ML systems in production
 </li>
 <li>
 Experience with LLMs, RAG pipelines, and modern AI frameworks
 </li>
 <li>
 Exposure to large-scale data platforms and distributed systems
 </li>
 <li>
 Experience working in cloud environments (multi-cloud preferred)
 </li>
 </ul>
 
 
 
 
 
 Skills &amp; Competencies:
 
 
 <ul>
 <li>
 AI/ML development (LLMs, RAG, model fine-tuning)
 </li>
 <li>
 Data engineering and pipeline development
 </li>
 <li>
 MLOps / LLMOps practices and tooling
 </li>
 <li>
 Backend development (Python and related frameworks)
 </li>
 <li>
 Distributed systems and scalable architectures
 </li>
 <li>
 AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain or similar)
 </li>
 <li>
 Data processing tools (e.g., Spark, Airflow, Prefect)
 </li>
 <li>
 Containerization and orchestration (Docker, Kubernetes)
 </li>
 <li>
 Cloud platforms (AWS, Azure, GCP)
 </li>
 <li>
 Observability and monitoring tools
 </li>
 </ul>
</div>

Sr. AI & Data Expert

MOZN

<div>
 
 About Mozn
 
 
 
 MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
 
 
 We&rsquo;re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
 
 
 If you&rsquo;re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
 
 
 
 About The Role
 
 
 
 The Mozn brand is alive within a plethora of stakeholder touchpoints and therefore the most suitable candidate for the Data Scientist I position would have an interest in Financial Fraud Detection, Sanction Screening, Know Your Customer (KYC) procedures, Anti-Money Laundering (AML) initiatives, and emerging Generative AI technologies. As a Data Scientist I, you will support the development of analytical and AI-driven solutions to help detect and prevent fraudulent activities and mitigate AML risks under close guidance.
 
 
 
 
 What you&rsquo;ll d
 
 
 
 
 o
 
 
 
 
 <ul>
 <li>
 Support the development of fraud detection, AML, and Generative AI use cases.
 </li>
 <li>
 Assist in building and testing ML and GenAI models (e.g., prompt engineering, RAG pipelines).
 </li>
 <li>
 Prepare, clean, and analyze structured and unstructured data.
 </li>
 <li>
 Support the training, evaluation, and deployment of ML models.
 </li>
 <li>
 Assist with experimentation using LLMs for tasks such as document analysis, alert summarization, or data enrichment.
 </li>
 <li>
 Execute assigned tasks within project plans under supervision.
 </li>
 <li>
 Stay informed about industry trends related to fraud, AML, and Generative AI.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Data Science, AI, Machine Learning, Mathematics, Statistics, or a related field.
 </li>
 <li>
 0&ndash;2 years of experience in data science or analytics.
 </li>
 <li>
 Basic understanding of ML concepts and exposure to Generative AI or LLMs.
 </li>
 <li>
 Proficiency in SQL and Python.
 </li>
 <li>
 Experience with data extraction, cleaning, and basic visualization.
 </li>
 <li>
 Familiarity with model evaluation and feature engineering concepts.
 </li>
 <li>
 Proficiency in English; Arabic is a plus.
 </li>
 <li>
 Strong problem-solving skills, attention to detail, and eagerness to learn.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
 </li>
 <li>
 You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
 </li>
 <li>
 The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
 </li>
 <li>
 You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
 </li>
 <li>
 We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.
 </li>
 </ul>
</div>

Data Scientist I

<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)

MASTER-WORKS

<div>Business Unit: Nabeh
Job Location: HQ
Job Purpose
Our subsidiary Nabeh is seeking for an experienced and highly skilled Software Testing, Senior Engineer. Responsible for designing, executing, and optimizing testing activities across AI and digital systems, ensuring high-quality delivery and supporting automation and performance initiatives.
Key Responsibilities<ul><li>
Design and maintain:
</li><li><ul><li>Test cases, test scenarios, and test data
</li></ul></li><li>Execute:
</li><li><ul><li>Functional, system, and integration testing
</li><li>API testing (Swagger, Postman)
</li></ul></li></ul><ul><li>Develop and maintain automation scripts (Selenium, Robot, SHAFT)
</li><li>Support performance testing execution (JMeter, Locust, Gatling, k6)
</li><li>Perform database validation and data consistency checks
</li><li>Validate AI outputs against defined scenarios and expected behavior
</li><li>Log, track, and manage defects with proper documentation
</li><li>Prepare test reports and execution evidence
</li><li>Collaborate with development, data, and AI teams
</li><li>Mentor and guide junior engineers
</li></ul>Qualifications &amp; Requirements<ul><li>
4&ndash;6+ years of QA experience
</li><li>Arabic Speaker (Mandatory)</li><li>
Strong hands-on experience in:
</li><li><ul><li>Test case design &amp; execution
</li><li>API and database testing
</li></ul></li></ul><ul><li>Working knowledge of automation frameworks
</li><li>Good understanding of performance testing concepts
</li><li>Exposure to AI systems or data-driven platforms (preferred)
</li><li>Experience in Agile environments
</li></ul>Certifications<ul><li>
ISTQB CTFL (Mandatory)
</li><li>ISTQB CTFL-AT (Preferred)
</li></ul>Language<ul><li>
Arabic (Native) &amp; English (Fluent)</li></ul></div>

Software Testing, Senior Engineer

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