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junior mechanical engineer

automation engineer reliability maintenance engineering

Cognizant

Job Summary
<br>This role is for a Lead Quality Engineer with twelve to fifteen years of experience responsible for driving advanced quality practices in office based day shift work with no travel requirement. The role focuses on test automation and intelligent validation using AI code assist tools context engineering Java Selenium RestAssured Cucumber and TestNG to ensure resilient and efficient delivery of enterprise software that supports robust business operations and reliable customer experiences.
<br>Responsibilities
<br>Telecom Domain is mandatory
<br>Drive comprehensive quality engineering strategies by designing and maintaining robust test automation frameworks using Java Selenium RestAssured Cucumber and TestNG to ensure consistent and efficient validation of complex enterprise applications
<br>Oversee end to end functional integration and regression testing cycles by coordinating test planning execution and reporting activities that provide clear visibility into product quality and release readiness for stakeholders
<br>Provide deep expertise in AI code assist tools by configuring refining and governing their usage to accelerate test script development reduce human errors and improve maintainability of automation assets
<br>Apply context engineering techniques to analyze business flows data dependencies and user scenarios in order to design intelligent test suites that closely mirror real world operations and uncover subtle defects early in the lifecycle
<br>Develop robust API testing solutions using RestAssured by defining reusable components data driven tests and validation logic that safeguard reliability performance and security across critical service interfaces
<br>Implement advanced Cucumber based behavior driven testing by collaborating on clear and concise scenarios that align with business expectations and enable transparent communication between technical and nontechnical stakeholders
<br>Enhance test execution efficiency by optimizing TestNG configurations parallel runs and reporting capabilities so that large and complex test sets can be executed reliably within project timelines
<br>Monitor and improve automation stability by analyzing failures refining object identification approaches and updating test data strategies to ensure resilient scripts that can withstand ongoing product changes
<br>Collaborate with cross functional teams by reviewing requirements user stories and design artifacts to clarify acceptance criteria and strengthen test coverage of features that directly support business and customer outcomes
<br>Provide quality insights through detailed defect analysis and root cause discussions that drive meaningful corrective actions and systemic improvements across development and testing practices
<br>Contribute to continuous delivery workflows by integrating automation suites into build pipelines and release processes so that quality gates are consistently enforced and feedback loops remain fast and actionable
<br>Support company goals of reliable and trusted digital experiences by ensuring that all deliverables pass rigorous quality checks that reduce production incidents and protect customer confidence in key business services
<br>Mentor team members on modern quality engineering techniques tool usage and coding practices that raise overall capability and help the organization adopt more scalable and sustainable automation approaches
<br>Qualifications
<br>Demonstrate strong proficiency in designing and maintaining Java based automation frameworks that integrate Selenium RestAssured Cucumber and TestNG to cover web API and end to end scenarios with high reliability
<br>Exhibit hands on experience using AI code assist tools to generate refactor and validate test code while applying sound judgment to maintain code quality readability and alignment with project standards
<br>Show practical application of context engineering principles by translating business processes data models and user journeys into focused test conditions that maximize defect detection and minimize redundant effort
<br>Bring solid experience in Selenium based user interface testing with a focus on robust locators modular page structures and data management approaches that keep scripts stable under frequent interface changes
<br>Apply detailed knowledge of RestAssured to design comprehensive API validation suites including status checks payload verification schema compliance and error handling scenarios relevant to enterprise services
<br>Utilize Cucumber effectively for behavior driven testing by writing clear scenarios step definitions and reusable contexts that align with business language and promote shared understanding among stakeholders
<br>Use TestNG features such as grouping prioritization and parallel execution to organize large test suites for optimal execution time and clear reporting of results against defined quality objectives
<br>Preferably bring experience in billing and revenue management domains by understanding rating invoicing payment and reconciliation processes and translating them into meaningful test scenarios that protect financial integrity
<br>Maintain strong skills in defect management test documentation and reporting tools to ensure traceability from requirements through test cases and defects supporting audits and continuous improvement initiatives
<br>Demonstrate the ability to operate effectively in a work from office day shift environment by collaborating closely with onsite teams and aligning testing activities with daily development and release rhythms
<br>Show commitment to quality culture by actively participating in retrospectives proposing process enhancements and promoting practices that reduce defects and improve reliability of software delivered to customers
<br>Exhibit strong communication and stakeholder engagement skills by explaining quality risks test strategies and results in accessible terms that support informed decision making across business and technology groups
<br><br>
Certifications Required
<br>Recommended certifications include ISTQB Advanced Test Automation Engineer and Java programming certification relevant to enterprise test automation.

Lead Quality Engineer

Qualcomm

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Information Technology Group, Information Technology Group &gt; IT Engineering
<p></p><p><b>General Summary:
</b></p><p></p><p><b>About the Role
</b></p><p>Qualcomm is leveraging its expertise in hardware‑accelerated AI to deliver powerful, energy‑efficient generative AI and computer vision workloads at rack‑scale in modern data centers. The Qualcomm Cloud AI team develops and operates a vertically integrated hardware and software platform for large‑scale AI inference acceleration across global deployments.
</p><p></p><p>We are seeking a Senior Data Center Operations Engineer to support Qualcomm&rsquo;s Cloud AI data center environments through hands-on administration of MAAS, virtual machines, server operating systems, and operational infrastructure. This role is responsible for reliable deployment, imaging, provisioning, troubleshooting, and maintenance of systems that support Cloud AI deployments.
</p><p></p><p>The role requires strong senior-level technical execution, practical troubleshooting judgment, coordination across internal and external teams, and disciplined ownership of documentation, inventory, and operational procedures.
</p><p></p><p><b>YOU MUST BE A SAUDI NATIONAL TO BE CONSIDERED FOR THIS ROLE
</b></p><p></p><p><b>Key Responsibilities will include
</b></p><p></p><p><b>Operational Excellence &amp; Reliability
</b></p><p></p><ul><li>Administer MAAS servers, including deployment configuration, bare-metal provisioning, image management, imaging workflows, and troubleshooting of provisioning issues.
</li><li>Provision, configure, and support virtual machines, including compute, memory, storage, and network resource allocation based on operational requirements.
</li><li>Install, patch, maintain, and troubleshoot server operating systems across bare-metal and virtualized environments.
</li></ul><p></p><p><b>Hardware &amp; Infrastructure Leadership
</b></p><p></p><ul><li>Support day-to-day server resources, storage coordination, and infrastructure incidents impacting Cloud AI data center operations.
</li><li>Troubleshoot server hardware, operating system, provisioning, VM, storage, and infrastructure issues, escalating when needed and supporting resolution through closure.
</li><li>Coordinate with HUMAIN, internal Qualcomm teams, and vendors to support deployments, maintenance activities, incident response, and operational follow-up.
</li><li>Maintain accurate system inventory, deployment records, configuration information, operational documentation, and standard operating procedures.
</li></ul><p></p><p><b>Automation, Tooling &amp; Continuous Improvement
</b></p><p></p><ul><li>Contribute to improvements in monitoring, alerting, ticketing, and operational workflows to reduce repeat issues and improve support efficiency.
</li><li>Develop and maintain runbooks, checklists, and troubleshooting procedures for MAAS, VM provisioning, OS maintenance, and infrastructure support activities.
</li><li>Participate in incident reviews and help translate lessons learned into practical operational process improvements.
</li></ul><p></p><p><b>Cross‑Functional Collaboration
</b></p><p></p><ul><li>Serve as a trusted technical partner to Cloud AI software, systems, security, supply chain, and facilities teams.
</li><li>Communicate complex operational issues, tradeoffs, and recommendations clearly to engineers, leadership, and external partners.
</li><li>Influence operational roadmaps and priorities through data‑driven insights and recommendations.
</li></ul><p></p><p><b>Required Qualifications &amp; Experience
</b></p><p>You demonstrate senior-level engineering ownership through hands-on technical depth, sound troubleshooting judgment, and the ability to execute independently across operational infrastructure responsibilities:
</p><p></p><ul><li>Hands-on experience administering MAAS or similar bare-metal provisioning platforms, including deployment, image management, and troubleshooting.
</li><li>Experience provisioning, configuring, and supporting virtual machines, including resource allocation and operational support.
</li><li>Strong Linux or server operating system administration experience, including installation, patching, maintenance, and troubleshooting.
</li><li>Ability to diagnose infrastructure incidents involving compute, storage, operating systems, provisioning workflows, and virtualization layers.
</li><li>Working knowledge of data center server hardware, storage coordination, networking basics, and operational support processes.
</li><li>Experience coordinating with internal engineering teams, external partners, and vendors to resolve operational issues and support deployments.
</li><li>Strong documentation discipline, including system inventory, configuration records, runbooks, and operational procedures.
</li><li>Clear written and verbal communication skills, with the ability to provide concise operational updates, document issues, and follow through on action items.
</li></ul><p></p><p><b>Nice‑to‑Have Experience
</b></p><p></p><ul><li>Experience designing or operating large‑scale AI inference platforms.
</li><li>Proficiency in Python, Bash, or similar scripting languages for automation.
</li><li>Experience with incident management, ticketing systems, and change management processes.
</li><li>Familiarity with hybrid cloud or cloud‑adjacent architectures.
</li><li>Exposure to data center compliance and security standards (e.g., ISO 27001, SOC 2).
</li></ul><p></p><p><b>Minimum Qualifications
</b></p><p></p><ul><li>Associate of Bachelor&rsquo;s degree in Electrical Engineering, Information Systems, Computer Science or related field with 6+ years of experience
</li><li>Significant hands‑on experience with computer hardware, servers, networking, and data center operations.
</li></ul><p></p><p><b>Preferred Qualifications
</b></p><p></p><ul><li>Industry certifications such as CompTIA Linux+, CCNA, CDCP, or equivalent demonstrated expertise.
</li></ul><p></p><p><b>Physical Requirements
</b></p><p></p><ul><li>Ability to frequently transport, install, and rack equipment weighing at least 25 lbs.
</li><li>Ability to work in data center environments involving standing, lifting, and equipment installation.
</li></ul><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>3+ years of IT-related work experience with a Bachelor's degree.
</li></ul>OR
<br>
5+ years of IT-related work experience without a Bachelor&rsquo;s degree.
<br>
<br>
<ul><li>Completed advanced degrees in a relevant field may be substituted for up to two years (Master&rsquo;s = one year, Doctorate = two years) of work experience.
</li></ul><p></p><p>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
</p><p></p><div><div><div><div><div><div><div><p><b>Applicants </b>: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</p></div></div></div></div></div></div></div><p></p><p>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

Data Center Operations Engineer, Senior – Cloud AI - Riyadh, KSA

HALA

<div>
 <p>
  <strong>
   Who Are We
  </strong>
 </p>
 <p>
  <br/>
  HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. HALA aims at empowering SMEs to start, run, and grow their businesses by providing them with cutting-edge financial and technological tools.
 </p>
 <p>
  <br/>
  HALA currently holds multiple entities in UAE, Saudi Arabia and Egypt (including HALA Payments and HALA Logistics) and offers solutions that enable merchants to digitize their payments as well as manage their sales and operations.
 </p>
 <p>
  <br/>
  Founded in 2017, HALA is currently licensed by the Saudi Arabian Central Bank.
 </p>
 <p>
  &nbsp;
 </p>
 Job Summary
 <p>
  The Software/AI Engineer , Compliance Technology is responsible for designing, developing, and maintaining technology, automation, and AI-enabled solutions that enhance the effectiveness, efficiency, and governance of Compliance operations. The role translates regulatory and business requirements into scalable technical solutions and supports areas including AML, KYC, fraud prevention, regulatory reporting, risk, and governance. The position also contributes to the responsible adoption of AI through appropriate governance, risk assessment, monitoring, and human oversight.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 Responsibilities&nbsp;
 <ul>
  <li>
   Design and develop technology solutions that automate and enhance Compliance processes.
  </li>
  <li>
   Build AI-powered tools to improve compliance monitoring, investigations, and regulatory reporting.
  </li>
  <li>
   Develop and maintain integrations, APIs, and internal applications supporting Compliance systems.
  </li>
  <li>
   Identify automation opportunities and translate compliance requirements into technical solutions.
  </li>
  <li>
   Implement AI, workflow automation, and RegTech solutions to improve operational efficiency.
  </li>
  <li>
   Develop dashboards and analytics that support compliance decision-making and regulatory reporting.
  </li>
  <li>
   Ensure solutions comply with cybersecurity, data privacy, and regulatory requirements.
  </li>
  <li>
   Collaborate with Compliance, Technology, Risk, and Information Security teams on system enhancements.
  </li>
  <li>
   Maintain and optimize compliance applications, ensuring reliability, performance, and scalability.
  </li>
  <li>
   Support audits and regulatory examinations by providing technical documentation and system evidence.
  </li>
  <li>
   Research and recommend emerging AI and compliance technologies to drive continuous improvement.
  </li>
  <li>
   Establish and maintain AI governance controls for Compliance use cases, ensuring responsible, transparent, and compliant use of AI technologies.
  </li>
  <li>
   Conduct AI risk assessments to identify and mitigate risks related to model accuracy, bias, data privacy, security, and regulatory compliance.
  </li>
  <li>
   Monitor and validate AI models and automated solutions on an ongoing basis to ensure accuracy, effectiveness, reliability, and appropriate human oversight.
  </li>
  <li>
   Ensure data quality and governance across Compliance systems and AI solutions, including data accuracy, integrity, access controls, and auditability.
  </li>
  <li>
   Leverage AI and automation to support regulatory change management, including identifying regulatory updates, assessing their impact, and supporting implementation and tracking of required actions.
  </li>
 </ul>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <strong>
  What We Offer You
  <br/>
 </strong>
 <strong>
  We believe you will love working at HALA!
 </strong>
 <ul>
  <li>
   We have an inclusive and diverse culture that encourages innovation and flexibility in remote, in-office, and hybrid work setups.
  </li>
  <li>
   We offer highly competitive compensation packages, including the potential for shares.
  </li>
  <li>
   We prioritize personal development and offer regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
  </li>
  <li>
   Join a talented team of over 30 nationalities working in 7 countries and gain valuable experience in an exciting industry.
  </li>
  <li>
   We offer autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.
  </li>
  <li>
   You will be given a lot of responsibility and trust.&nbsp;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>
 </ul>
 &nbsp;
 <strong>
  If you think you have what it takes to join a remarkable team #apply_now&nbsp;
 </strong>
 <p>
  &nbsp;
 </p>
</div>


AI & System Engineer

Tabby | تابي

<div>
 <strong>
  Department:
 </strong>
 Customer Happiness, Engineering
 <br/>
 <br/>
 <strong>
  Employment Type:
 </strong>
 Internship
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 KSA
 <br/>
 <br/>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 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/>
 <br/>
 This internship is not educational by default. It is an engineering-adjacent role with real production impact.
 <br/>
 <br/>
 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/>
 <br/>
 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.
 <br/>
 <br/>
 Key Responsibilities
 <br/>
 <br/>
 This is not a demo or experimentation-only role. Interns work on real agents, workflows, and internal tools.
 <br/>
 <br/>
 <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>
  <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>
  <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>
  <li>
   Expert-level knowledge of LLMs, agent frameworks, or prompt engineering
  </li>
  <li>
   Prior professional AI, automation, or platform engineering experience
  </li>
  <li>
   Mastery of all listed no-code platforms or LLM tooling
  </li>
  <li>
   Deep knowledge of ML internals, model training, or RAG architectures
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Skills, Knowledge &amp; Expertise
 <br/>
 <br/>
 <ul>
  <li>
   Saudi nationals only
  </li>
  <li>
   Self-funded internship by Tabby
  </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.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Format
 <br/>
 <br/>
 <ul>
  <li>
   Paid internship
  </li>
  <li>
   Full integration into the automations building team
  </li>
  <li>
   Distributed engineering team across multiple countries
  </li>
  <li>
   Open to Saudi nationals (Saudi passport required); location flexible &mdash; candidates may be based outside KSA
  </li>
  <li>
   Office-first in Riyadh where possible
  </li>
  <li>
   Clear path to a junior AI automation, no-code engineer, or platform role based on performance
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 This internship is intentionally demanding and designed for candidates aiming for fast professional growth in AI agents and automation engineering.
</div>


AI Intern

<div>
 <p>
  <strong>
   Department:
  </strong>
  Customer Happiness, Engineering
 </p>
 <p>
  <strong>
   Location:
  </strong>
  KSA
  <br/>
  <br/>
 </p>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 About the companyTabby 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/>
 <br/>
 This internship is not educational by default. It is an engineering-adjacent role with real production impact.
 <br/>
 <br/>
 ContextThe 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/>
 <br/>
 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.
 <br/>
 <br/>
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 What you will doThis is not a demo or experimentation-only role. Interns work on real agents, workflows, and internal tools.
 <br/>
 <br/>
 <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>
 Required
 <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>
 Strong plus
 <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>
 What we do not expect
 <ul>
  <li>
   Expert-level knowledge of LLMs, agent frameworks, or prompt engineering
  </li>
  <li>
   Prior professional AI, automation, or platform engineering experience
  </li>
  <li>
   Mastery of all listed no-code platforms or LLM tooling
  </li>
  <li>
   Deep knowledge of ML internals, model training, or RAG architectures
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills, Knowledge &amp; Expertise
  <br/>
  <br/>
 </strong>
 Eligibility
 <ul>
  <li>
   Saudi nationals only
  </li>
  <li>
   Self-funded internship by Tabby
  </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.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Format
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Paid internship
  </li>
  <li>
   Full integration into the automations building team
  </li>
  <li>
   Distributed engineering team across multiple countries
  </li>
  <li>
   Open to Saudi nationals (Saudi passport required); location flexible &mdash; candidates may be based outside KSA
  </li>
  <li>
   Office-first in Riyadh where possible
  </li>
  <li>
   Clear path to a junior AI automation, no-code engineer, or platform role based on performance
  </li>
 </ul>
 This internship is intentionally demanding and designed for candidates aiming for fast professional growth in AI agents and automation engineering.
 <br/>
 <br/>
</div>


MASTER-WORKS

<div><p>Master Works is looking for an <b>Agentic AI, Engineer </b>to join our growing team and design, build, and deploy agentic AI systems that can plan, reason, and act. The role covers both single-agent and multi-agent systems, as well as orchestration of workflows involving retrieval-augmented generation (RAG), context engineering, reasoning, tool calling, memory, and inter-agent communication. This role is ideal for a strong software engineer with hands-on AI/ML development experience and a passion for transforming generative AI models into reliable, goal-driven systems capable of solving complex, real-world business problems.</p><p></p>
Key Responsibilities:<p></p><ul><li>
Architect, build, and deploy agentic AI systems that integrate AI agents with foundation models, enterprise systems, third-party tools, and APIs using established agentic frameworks or custom-built orchestrators.</li><li>
Build and maintain retrieval-augmented generation (RAG), memory, and reasoning pipelines that ground agent decisions in reliable, real-world data and enable persistent, contextual, and adaptive behavior.</li><li>
Design single-agent and multi-agent workflows, including planning, delegation, tool selection, handoffs, inter-agent communication, and human-in-the-loop controls.</li><li>
Optimize orchestration and reasoning performance while balancing autonomy, latency, cost, interpretability, reliability, and maintainability.</li><li>
Collaborate with Generative AI engineers, application engineers, MLOps engineers, and product teams to move agentic AI solutions from prototype to production.</li><li>
Monitor, evaluate, and benchmark agent performance, and help ensure AI systems are safe, accurate, trustworthy, observable, and capable of delivering a high-quality user experience.</li><li>
Document agent architectures, communication flows, guardrails, context-engineering strategies, memory design, tool interfaces, and orchestration logic to ensure clarity and reproducibility.</li><li>
Stay current with advances in agentic AI, multi-agent orchestration, RAG, model-context protocols, cognitive architectures, evaluation methods, and AI safety mechanisms.</li><li>
Collaborate with cross-functional teams to design and deliver complete AI solutions for customers.</li></ul><br>
<b>
Requirements</b><br>
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field.</li><li>
2+ years of hands-on experience developing agentic AI systems, LLM-powered applications, or advanced Generative AI solutions.</li><li>
Preferably 5+ years of overall professional software engineering experience</li><li>
Contributions to open-source agentic AI frameworks, orchestration platforms, evaluation tooling, or agent communication protocols.</li><li>
Experience building microservices and deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).</li><li>
Experience with AI safety, guardrails, observability, traceability, evaluation, and explainability for agentic AI systems.</li><li>
Experience deploying LLM or agentic workloads in production using containers, Kubernetes, CI/CD pipelines, and modern MLOps or LLMOps practices.</li></ul><p></p><p><b>
Job Location: </b>HQ</p></div>

Agentic AI, Engineer

Accenture

<div><div><div><p><b>YOU ARE</b></p></div><div><p>
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps &amp; MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.</p></div><div><p><b>
THE WORK</b></p></div><div><ul><li><p>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</p></li></ul></div><div><ul><li><p>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</p></li></ul></div><div><ul><li><p>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</p></li></ul></div><div><ul><li><p>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</p></li></ul></div></div><div><div><ul><li><p>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</p></li></ul></div><div><ul><li><p>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</p></li></ul></div><div><ul><li><p>
Justify the value of model approaches in business problems</p></li></ul></div><div><ul><li><p>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</p></li></ul></div></div></div>
<br>
<div><div><p><b>EDUCATION</b></p></div><div><ul><li><ul><li>Bachelor's Degree or equivalent</li></ul></li></ul></div><div><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p></div><div><ul><li><p>
Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</p></li></ul></div><div><ul><li><p>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</p></li></ul></div><div><ul><li><p>
Hands-on experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</p></li></ul></div><div><ul><li><p>
Experience in building and deploying AI/ML based software to a cloud environment.</p></li></ul></div><div><p><b>
PREFERRED QUALIFICATION</b></p></div><div><ul><li><p>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..</p></li></ul></div><div><ul><li><p>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</p></li></ul></div><div><ul><li><p>
Experience with the following programming languages: Python, C++, Java, R, SQL</p></li></ul></div><div><ul><li><p>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</p></li></ul></div><div><ul><li><p>
Strong client-facing skillsets in a consulting environment</p></li></ul></div><div><ul><li><p>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</p></li></ul></div><div><ul><li><p>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</p></li></ul></div><div><ul><li><p>
MS or PhD in related field preferred (computer science, engineering, etc.)</p></li></ul></div></div>

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