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Future Group Language Solutions

<div>
 
 About The Role
 
 
 
 We are looking for an
 
 Applied AI Engineer
 
 to design, build, and deploy intelligent AI solutions that solve real business challenges. In this role, you'll work with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), GraphRAG, AI agents, and knowledge graphs to create scalable, production-ready AI applications.
 
 
 This is an
 
 AI-first engineering role
 
 , where leveraging AI development tools such as ChatGPT, Cursor, GitHub Copilot, Claude, or Windsurf is an essential part of the development workflow.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and deploy AI-powered applications using LLMs.
 </li>
 <li>
 Build and optimize RAG and GraphRAG pipelines.
 </li>
 <li>
 Develop AI agents and multi-agent workflows for business automation.
 </li>
 <li>
 Design and manage knowledge graphs using GraphDB technologies.
 </li>
 <li>
 Integrate enterprise data sources with AI applications.
 </li>
 <li>
 Engineer prompts, workflows, and agent orchestration for reliable AI systems.
 </li>
 <li>
 Evaluate and optimize AI models for quality, latency, scalability, and cost.
 </li>
 <li>
 Build production-ready APIs and AI services.
 </li>
 <li>
 Collaborate with cross-functional teams to deliver AI-driven products.
 </li>
 <li>
 Stay up to date with the latest AI models, frameworks, and best practices.
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, AI, or a related field.
 </li>
 <li>
 3+ years of experience developing AI-powered or data-intensive applications.
 </li>
 <li>
 Strong proficiency in Python.
 </li>
 <li>
 Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Gemini, or similar).
 </li>
 <li>
 Experience implementing Retrieval-Augmented Generation (RAG).
 </li>
 <li>
 Experience with Graph Databases such as Neo4j, Amazon Neptune, Memgraph, or GraphDB.
 </li>
 <li>
 Familiarity with vector databases such as Pinecone, Qdrant, Weaviate, Milvus, or pgvector.
 </li>
 <li>
 Experience integrating AI models through APIs and SDKs.
 </li>
 <li>
 Solid understanding of REST APIs, Git, Docker, and cloud platforms (Azure, AWS, or GCP).
 </li>
 <li>
 Strong analytical, debugging, and problem-solving skills.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with GraphRAG architectures.
 </li>
 <li>
 Knowledge of AI agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK.
 </li>
 <li>
 Experience with Model Context Protocol (MCP).
 </li>
 <li>
 Prompt engineering and AI evaluation frameworks.
 </li>
 <li>
 Knowledge of semantic search and hybrid retrieval.
 </li>
 <li>
 Experience with FastAPI, Django, or Flask.
 </li>
 <li>
 Familiarity with Kubernetes, CI/CD pipelines, and microservices.
 </li>
 <li>
 Experience building knowledge graphs and ontology design.
 
 
 
 </li>
 </ul>
 What We Offer
 
 
 <ul>
 <li>
 Opportunity to build cutting-edge AI products.
 </li>
 <li>
 Collaborative and innovative engineering environment.
 </li>
 <li>
 Exposure to the latest AI technologies and frameworks.
 </li>
 <li>
 Professional growth and continuous learning opportunities.
 </li>
 <li>
 Competitive salary and benefits package.
 
 
 
 </li>
 </ul>
 Join Our Team
 
 
 If you're passionate about building practical AI applications, enjoy working with the latest AI technologies, and thrive in an AI-first development environment, we'd love to hear from you!
</div>

Applied AI Engineer (AI-First / Vibe Coding)

UR SUPPORT

<div>
 
 Role Purpose
 
 
 
 The QA Engineer will be responsible for protecting the quality, reliability, security, and usability of our HR platform. The role will combine strong manual testing capabilities with progressive automation of critical product, API, integration, and regression test scenarios.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Review product requirements, user stories, process flows, and acceptance criteria before development begins.
 </li>
 <li>
 Create and maintain test strategies, test plans, test cases, test data, checklists, and traceability documentation.
 </li>
 <li>
 Perform functional, regression, integration, API, database, usability, compatibility, and exploratory testing.
 </li>
 <li>
 Test HRMS, payroll, employee self-service, manager self-service, attendance, workflow, notification, reporting, and administrative modules.
 </li>
 <li>
 Validate integrations with Saudi government, banking, payroll, identity, ERP, payment, and enterprise platforms.
 </li>
 <li>
 Test successful and unsuccessful integration scenarios, including invalid data, timeout conditions, duplicate requests, API failures, retry logic, and reconciliation processes.
 </li>
 <li>
 Perform API testing using Postman or equivalent tools.
 </li>
 <li>
 Validate database records and business rules using SQL queries.
 </li>
 <li>
 Design and maintain automated tests using Playwright, Cypress, Selenium, or an equivalent framework.
 </li>
 <li>
 Prioritise automation for critical business processes, high-risk integrations, repetitive regression scenarios, and frequently released functionality.
 </li>
 <li>
 Integrate automated tests into CI/CD pipelines where appropriate.
 </li>
 <li>
 Document defects with clear reproduction steps, expected results, actual results, evidence, severity, and business impact.
 </li>
 <li>
 Work closely with developers to investigate defects and verify corrective actions.
 </li>
 <li>
 Support User Acceptance Testing and release-readiness activities.
 </li>
 <li>
 Establish release quality gates and provide clear recommendations regarding production deployment.
 </li>
 <li>
 Monitor production issues and convert recurring defects into permanent regression tests.
 </li>
 <li>
 Use AI-assisted tools to improve test-case generation, exploratory testing, automation scripting, defect analysis, and test-data preparation.
 </li>
 <li>
 Independently validate AI-generated test cases and automation scripts before use.
 </li>
 <li>
 Support competitive product analysis by testing new our platform capabilities against expected Saudi market standards and customer requirements.
 
 
 </li>
 </ul>
 
 Requirements And Qualifications
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in software quality assurance.
 </li>
 <li>
 Strong experience in manual testing, including functional, regression, integration, API, database, and User Acceptance Testing.
 </li>
 <li>
 Experience designing test strategies, test plans, test cases, test data, and defect reports.
 </li>
 <li>
 Strong experience with Postman or similar API-testing tools.
 </li>
 <li>
 Good working knowledge of SQL and relational databases.
 </li>
 <li>
 Experience with automation testing tools such as Playwright, Cypress, or Selenium.
 </li>
 <li>
 Experience automating web applications and RESTful APIs is highly preferred.
 </li>
 <li>
 Familiarity with JavaScript or TypeScript for test automation is preferred.
 </li>
 <li>
 Experience working with Agile/Scrum teams throughout the software development lifecycle.
 </li>
 <li>
 Experience with Git, CI/CD pipelines, issue-tracking systems, and test-management tools.
 </li>
 <li>
 Previous experience testing cloud-based, multi-tenant SaaS or enterprise applications is highly preferred.
 </li>
 <li>
 Experience testing HRMS, payroll, ERP, workforce management, or enterprise workflow applications is a strong advantage.
 </li>
 <li>
 Experience testing external API integrations, government platforms, payment systems, or banking integrations is preferred.
 </li>
 <li>
 Understanding of Saudi HR, payroll, employment, and regulatory business processes is considered a strong advantage.
 </li>
 <li>
 Experience using AI-assisted testing or coding tools for test generation, automation, and defect analysis.
 </li>
 <li>
 Strong attention to detail, analytical thinking, communication, documentation, and problem-solving skills.
 </li>
 <li>
 Ability to challenge unclear requirements and identify functional, technical, usability, and business-process risks.
 </li>
 </ul>
</div>

QA Engineer - Manual and Automation

CNTXT AI

<div>
 
 About Munsit AI
 
 
 Munsit AI is building AI-powered products that transform how businesses create, collaborate, and scale. We're looking for a data-driven Web/Growth Engineer who combines strong software engineering skills with a growth mindset to optimise user acquisition, activation, engagement, and conversion across our digital products.
 
 
 Role Overview
 
 
 As a Web/Growth Engineer, you'll bridge engineering, marketing, and product to build high-performing web experiences that drive measurable business growth. You'll own experimentation, landing page development, analytics implementation, SEO improvements, and conversion optimization while ensuring exceptional performance and user experience.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Build, maintain, and optimize high-converting marketing websites and landing pages.
 
 </li>
 <li>
 
 Develop scalable frontend experiences using modern JavaScript frameworks.
 
 </li>
 <li>
 
 Design and implement A/B tests and growth experiments to improve conversion rates.
 
 </li>
 <li>
 
 Collaborate with Product, Design, and Marketing teams to rapidly launch campaigns and features.
 
 </li>
 <li>
 
 Optimize website performance, Core Web Vitals, and overall user experience.
 
 </li>
 <li>
 
 Implement analytics, event tracking, and conversion measurement across web properties.
 
 </li>
 <li>
 
 Improve technical SEO, site architecture, structured data, and page indexing.
 
 </li>
 <li>
 
 Integrate CRM, marketing automation, and third-party growth tools.
 
 </li>
 <li>
 
 Monitor user behavior using analytics and session recording tools to identify optimization opportunities.
 
 </li>
 <li>
 
 Automate growth workflows and improve marketing operations through engineering solutions.
 
 </li>
 <li>
 
 Ensure websites are secure, responsive, accessible, and scalable.
 
 
 
 </li>
 </ul>
 
 Requirements
 
 <ul>
 <li>
 
 Bachelor's degree in Computer Science, Software Engineering, or a related field.
 
 </li>
 <li>
 
 5+ years of relevant experience.
 
 </li>
 <li>
 
 Strong proficiency in JavaScript/TypeScript.
 
 </li>
 <li>
 
 Experience with React, Next.js, or similar modern frontend frameworks.
 
 </li>
 <li>
 
 Experience implementing analytics tools such as Google Analytics 4, Mixpanel, Amplitude, or PostHog.
 
 </li>
 <li>
 
 Hands-on experience with A/B testing platforms and experimentation frameworks.
 
 </li>
 <li>
 
 Understanding of SEO best practices, technical SEO, and Core Web Vitals.
 
 </li>
 <li>
 
 Familiarity with REST APIs, GraphQL, and third-party integrations.
 
 </li>
 <li>
 
 Strong problem-solving skills with a data-driven approach to decision-making.
 
 
 
 </li>
 </ul>
</div>

Web/Growth Engineer

Valeo

<div>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Deploy and maintain secure cloud infrastructure primarily on GCP (Google Cloud Platform) and AWS, ensuring seamless integration between services.
 </li>
 <li>
 Manage and optimize GKE (Google Kubernetes Engine) clusters for high-availability AI applications and microservices.
 </li>
 <li>
 Infrastructure as Code: Build and enforce Terraform strategies to provision and manage infrastructure, ensuring environments are reproducible and version-controlled.
 </li>
 <li>
 CI/CD &amp; Software Verification: Design and implement advanced CI/CD workflows using GitHub Actions, moving beyond simple deployments to create intelligent automation.
 </li>
 <li>
 Build robust verification pipelines that include automated testing, linting, security scanning, and quality gates before production release.
 </li>
 <li>
 Streamline the release process for backend and frontend applications, ensuring "one-click" reliability.
 </li>
 <li>
 Oversee the deployment, maintenance, and backup strategies for databases.
 </li>
 <li>
 Implement comprehensive monitoring and logging solutions (Prometheus, Grafana, Cloud Ops, Cloud Monitoring) to ensure system health, performance, and rapid incident response.
 </li>
 <li>
 Implement security best practices (IAM, VPC configuration, encryption) to protect sensitive AI data and intellectual property.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 Education &amp; Experience
 
 
 
 
 <ul>
 <li>
 B.Sc. or M.Sc. in Computer Science, Computer Engineering, or a related technical field.
 </li>
 <li>
 5+ years of relevant experience in DevOps, Cloud Engineering, or Site Reliability Engineering (SRE).
 </li>
 <li>
 Proven experience acting as a Senior or Lead engineer, guiding architectural decisions.
 
 
 </li>
 </ul>
 
 
 Technical Requirements
 
 
 
 
 <ul>
 <li>
 Advanced hands-on experience with GCP (specifically GKE, VPC, IAM) and a working knowledge of AWS.
 </li>
 <li>
 Proven ability to design and implement robust, scalable, and secure cloud architectures.
 </li>
 <li>
 Mastery of Docker and Kubernetes administration.
 </li>
 <li>
 Strong proficiency in Terraform.
 </li>
 <li>
 Expert knowledge of GitHub Actions for building, test, build, and deploy pipelines.
 </li>
 <li>
 Experience managing PostgreSQL and ClickHouse databases.
 </li>
 <li>
 Deep understanding of Linux System Administration.
 </li>
 <li>
 Experience with AI/ML lifecycle tools (e.g., Kubeflow, MLflow, Vertex AI).
 </li>
 <li>
 Strong proficiency in Python and Bash scripting.
 </li>
 <li>
 Familiarity with DevSecOps tools and practices.
 </li>
 <li>
 Bonus: Official GCP Certifications (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer) and Kubernetes Certifications (e.g., CKA, CKAD, CKS) are highly preferred.
 </li>
 <li>
 Bonus: Knowledge of Javascript/Node.js is a strong plus.
 
 
 </li>
 </ul>
 
 
 Soft Skills &amp; Mindset
 
 
 
 
 <ul>
 <li>
 Ability to design long-term solutions rather than quick fixes.
 </li>
 <li>
 Excellent ability to explain complex cloud concepts to Data Scientists and business stakeholders.
 </li>
 <li>
 Comfortable working in a fast-paced environment with evolving requirements.
 </li>
 <li>
 Fluent English is a must.
 </li>
 </ul>
</div>

Senior DevOps Engineer, AI4ALL

Henkel

<div>
 
 About this Position
 
 The Data Engineer supports the development and operation of Henkel&rsquo;s enterprise metadata platform, DataHub. The role focuses on building scalable data engineering and governance solutions that connect key enterprise platforms into one centralized ecosystem serving global data consumers.
 
 
 As part of a hands-on engineering environment, the position contributes to data quality, automation, and cloud-based capabilities that strengthen how data is discovered, understood, and trusted across Henkel.
 
 
 
 What You&acute;ll Do
 
 
 
 <ul>
 <li>
 Build and maintain scheduled metadata ingestion pipelines integrating platforms such as Databricks Unity Catalog, Power BI, SAP, and Azure Synapse into DataHub
 </li>
 <li>
 Support and enhance governance automation solutions covering dataset compliance, ownership, descriptions, lineage, and automated tagging
 </li>
 <li>
 Develop and improve data quality and completeness scoring capabilities across the enterprise data landscape
 </li>
 <li>
 Work directly with DataHub SDKs, REST APIs, and GraphQL APIs to support metadata operations and integrations
 </li>
 <li>
 Contribute to AI-enabled metadata access capabilities supporting intelligent assistants and modern AI solutions
 </li>
 <li>
 Build and maintain data lineage between source systems and downstream consumers
 </li>
 <li>
 Develop scalable cloud-native solutions running on Azure Kubernetes Service (AKS)
 </li>
 <li>
 Collaborate with global and cross-functional teams to support scalable and reliable enterprise data solutions
 </li>
 <li>
 Support engineering best practices including testing, monitoring, and continuous platform enhancements
 
 
 </li>
 </ul>
 
 What makes you a good fit
 
 
 
 <ul>
 <li>
 </li>
 <li>
 Strong experience with Python and SQL, including working with analytical databases such as PostgreSQL or Databricks
 </li>
 <li>
 Experience building and maintaining scalable and scheduled data pipelines, including automation, error handling, and reliability practices
 </li>
 <li>
 Understanding of REST APIs, GraphQL, and system integrations
 </li>
 <li>
 Experience with cloud platforms and services, preferably Microsoft Azure and Databricks
 </li>
 <li>
 Familiarity with containerization technologies and Kubernetes-based environments
 </li>
 <li>
 Experience with metadata platforms or data governance solutions such as DataHub or similar tools is considered a plus
 </li>
 <li>
 Familiarity with CI/CD pipelines, infrastructure automation, and modern engineering practices is an advantage
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills
 </li>
 <li>
 Ability to work independently and collaborate effectively with technical and non-technical stakeholders
 </li>
 <li>
 Passion for data quality, governance, automation, and scalable engineering solutions
 </li>
 <li>
 Comfortable working with modern technologies, open-source solutions, and continuously learning new concepts and tools
 
 
 </li>
 </ul>
 
 Some perks of joining Henkel
 
 
 
 <ul>
 <li>
 Flexible work scheme with flexible hours, hybrid work model, and work from anywhere policy for up to 30 days per year
 </li>
 <li>
 Diverse national and international growth opportunities
 </li>
 <li>
 Global wellbeing standards with health and preventive care programs
 </li>
 <li>
 Gender-neutral parental leave for a minimum of 8 weeks
 </li>
 <li>
 Employee Share Plan with voluntary investment and Henkel matching shares
 </li>
 <li>
 Comprehensive Health Insurance for employee + dependents
 </li>
 <li>
 Employee Assistance Programme provides a wide range of mental health and wellbeing benefits
 
 
 </li>
 </ul>
 At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We look for a diverse team of individuals who possess different backgrounds, experiences, personalities and mindsets.
</div>

Data Engineer

<div>
 
 
 About the Role
 
 
 
 
 
 
 We are seeking an experienced AI/ML Developer Level II to join our Innovation &amp; Software Solutions team. In this role, you will be responsible for designing, developing, deploying, and optimizing enterprise-grade conversational AI solutions using the RASA framework, Python, and Google Cloud Platform (GCP). Working closely with cross-functional teams, you will build scalable, production-ready virtual assistants and intelligent automation solutions while driving continuous improvements in machine learning models, NLP performance, and MLOps practices. This is an excellent opportunity for a proactive developer who is passionate about conversational AI, cloud technologies, and delivering innovative AI-powered solutions at scale.
 
 
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Design, develop, and maintain enterprise-grade conversational AI solutions using RASA Open Source and RASA Pro/X.
 </li>
 <li>
 Develop complex dialogue flows, NLU pipelines, custom actions, stories, and rules.
 </li>
 <li>
 Train, evaluate, fine-tune, and optimize NLP models to improve chatbot performance, intent recognition, entity extraction, and user experience.
 </li>
 <li>
 Build clean, scalable, and maintainable backend services and APIs using Python.
 </li>
 <li>
 Deploy, monitor, and manage AI applications on Google Cloud Platform (GKE, Cloud Run, Compute Engine, Pub/Sub, Vertex AI, Dialogflow, Cloud Speech-to-Text, and Text-to-Speech).
 </li>
 <li>
 Integrate conversational AI solutions with enterprise systems and third-party services.
 </li>
 <li>
 Contribute to CI/CD pipelines, automated testing, model versioning, and MLOps best practices.
 </li>
 <li>
 Analyze conversational data using BigQuery and leverage Cloud Storage for managing training datasets and model artifacts.
 </li>
 <li>
 Collaborate within an Agile development environment and mentor junior team members when needed.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
 </li>
 <li>
 Strong hands-on experience with Python and software engineering best practices.
 </li>
 <li>
 Proven experience developing conversational AI solutions using RASA.
 </li>
 <li>
 Hands-on experience with Google Cloud Platform (GCP) services.
 </li>
 <li>
 Strong understanding of Natural Language Processing (NLP) concepts, including intent classification, entity recognition, dialogue management, and context handling.
 </li>
 <li>
 Experience working with machine learning frameworks such as spaCy, scikit-learn, or Transformers.
 </li>
 <li>
 Proficiency with Git and collaborative software development workflows.
 </li>
 <li>
 Excellent analytical, problem-solving, and communication skills.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 
 
 
 <ul>
 <li>
 Experience with Docker and Kubernetes.
 </li>
 <li>
 Knowledge of Terraform or other Infrastructure-as-Code tools.
 </li>
 <li>
 Experience implementing CI/CD pipelines and MLOps workflows.
 </li>
 <li>
 Google Cloud certifications, particularly Professional Machine Learning Engineer, are highly desirable.
 </li>
 </ul>
 
 
</div>

AI/ML Developer Level II

<div>
 
 
 We're Hiring: AI &amp; Automation Analyst
 
 
 
 We are looking for an
 
 AI &amp; Automation Analyst
 
 to join our team. This is an exciting opportunity for professionals with a passion for Artificial Intelligence, Machine Learning, and Automation to contribute to innovative solutions that enhance business processes and drive digital transformation.
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Analyze business needs and identify opportunities for AI and automation.
 </li>
 <li>
 Design, develop, and implement AI solutions and automated workflows.
 </li>
 <li>
 Build and deploy machine learning models and automation scripts.
 </li>
 <li>
 Collaborate with cross-functional teams to deliver business-driven technology solutions.
 </li>
 <li>
 Prepare, analyze, and manage data to support AI initiatives.
 </li>
 <li>
 Monitor, test, and continuously improve AI and automation solutions.
 </li>
 <li>
 Ensure compliance with data privacy and security standards.
 </li>
 </ul>
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Data Science, or a related field.
 </li>
 <li>
 1&ndash;3 years of experience in AI technologies, Machine Learning, and Automation.
 </li>
 <li>
 Proficiency in Python, R, or Java.
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills.
 </li>
 <li>
 Experience with automation tools and integrating AI solutions into business processes.
 </li>
 <li>
 Certifications in AI, Machine Learning, RPA, or PMP are considered an advantage.
 </li>
 <li>
 Experience within the FMCG industry is a plus.
 </li>
 </ul>
 
 
 
</div>

AI and Automation Analyst

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