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ai automation engineer light

Valeo

<div>
 Responsibilities Cross-Disciplinary Automation
 
 :
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling: Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 : Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 : Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance:
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 : Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction: Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance: Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration: Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment: Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 
 Programming &amp; Scripting
 
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM: ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling:
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
</div>

AI & Automation Engineer, LIGHT

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 Responsibilities Cross-Disciplinary Automation
 
 ~
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling~ Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 ~ Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 ~ Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance~
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 ~ Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction~ Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance~ Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration~ Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment~ Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 Programming &amp; Scripting~
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM~ ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling~
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
 
 
 
 Position~
 
 
 
 AI4all, Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 GTSC Software
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-04-07
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

Fotopia Technologies

<div>
 🚀
 
 We&rsquo;re Hiring: DevOps Engineer | Fotopia Technologies
 
 
 
 Fotopia Technologies is growing, and we are looking for a talented
 
 DevOps Engineer
 
 to join our team as we build the next generation of
 
 AI-powered document automation, intelligent capture, and enterprise transformation platforms
 
 .
 
 
 This is not a routine DevOps role. You will be part of a team building serious enterprise platforms used for high-volume document processing, AI/OCR pipelines, SaaS deployments, and mission-critical customer environments.
 
 
 What you&rsquo;ll work on
 
 
 You will help us design, automate, secure, and scale our development and deployment infrastructure across multiple Fotopia products, including our AI-driven IDP platforms.
 
 
 Key responsibilities
 
 
 ✅ Build and manage CI/CD pipelines
 
 
 ✅ Support cloud and on-premise deployments
 
 
 ✅ Manage Docker-based environments and deployment automation
 
 
 ✅ Work with development teams to improve release quality and speed
 
 
 ✅ Support monitoring, logging, backup, and infrastructure reliability
 
 
 ✅ Help enforce DevOps governance, environment separation, and release controls
 
 
 ✅ Contribute to scalable infrastructure for AI, OCR, and enterprise platforms
 
 
 We&rsquo;re looking for someone with
 
 
 🔹 Strong experience in DevOps, CI/CD, Docker, and deployment automation
 
 
 🔹 Good knowledge of Linux, scripting, Git, and cloud environments
 
 
 🔹 Experience with Azure DevOps is a must have.
 
 
 🔹 Understanding of production environments, security, monitoring, and release management
 
 
 🔹 A practical mindset, strong ownership, and the ability to work with developers, architects, and project teams
 
 
 🔹 Passion for building reliable systems, not just running scripts
 
 
 Why join Fotopia?
 
 
 At Fotopia, you will work on real enterprise products, not just internal tools. You will be part of a company building advanced solutions in
 
 AI, document intelligence, enterprise automation, and digital transformation
 
 for customers across the region.
 
 
 We are looking for someone who wants to grow with us, take ownership, and play a key role in shaping the infrastructure behind our next-generation platforms.
</div>

DevOps Engineer

Arrow Components

<div>
 
 Position
 
 
 
 Senior Software Quality Engineer
 
 
 
 Job Description
 
 
 
 We&rsquo;re looking for a
 
 Senior Software Quality Engineer
 
 with strong experience in manual, automation, performance, and API testing, along with a passion for using
 
 AI/ML to enhance software testing
 
 . You&rsquo;ll be part of an Agile team focused on delivering high-quality products faster and smarter.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Plan, design, and execute manual and automated test cases based on requirements, user stories, and acceptance criteria.
 </li>
 <li>
 Develop and maintain test automation frameworks across UI and API platforms.
 </li>
 <li>
 Perform API testing using tools like Postman, RestAssured, or similar.
 </li>
 <li>
 Develop and maintain performance testing using tools such as JMeter, Gatling, or LoadRunner; analyze performance metrics and suggest improvements.
 </li>
 <li>
 Apply AI/ML technologies techniques to improve testing practices, such as:
 </li>
 <ul>
 <li>
 AI-assisted test case generation
 </li>
 <li>
 Test impact analysis
 </li>
 <li>
 Intelligent test prioritization
 </li>
 <li>
 Self-healing automation scripts
 </li>
 <li>
 Predictive defect analysis
 </li>
 </ul>
 <li>
 Collaborate with developers, product owners, and business analysts in Agile ceremonies including sprint planning, reviews, and retrospectives.
 </li>
 <li>
 Contribute to and enforce quality best practices, including shift-left testing and test strategy planning.
 </li>
 <li>
 Investigate, debug, and triage issues; perform root cause analysis and track defect trends.
 </li>
 <li>
 Continuously explore and evaluate new tools and techniques to optimize test coverage and cycle time.
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 
 
 <ul>
 <li>
 3+ years in QC with expertise in manual, automation, API, and performance testing.
 </li>
 <li>
 Hands-on experience with tools like Selenium, Playwright, JMeter, and Postman.
 </li>
 <li>
 Proficient in scripting/programming languages like Python, Java, or JavaScript.
 </li>
 <li>
 Working knowledge of AI/ML concepts, especially as applied to testing (e.g., pattern detection, test impact analysis).
 </li>
 <li>
 Experience using or evaluating AI-based testing tools or frameworks.
 </li>
 <li>
 Solid understanding of Agile/Scrum practices and CI/CD pipelines.
 </li>
 <li>
 Strong analytical, debugging, and problem-solving skills.
 
 
 </li>
 </ul>
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Senior Software Quality Engineer

Flatgigs

<div>
 
 The Role
 
 
 
 The Forward Deployed AI Engineer will work directly with clients and senior engineers to build AI-powered systems inside real enterprise environments. This role is ideal for a strong junior engineer who wants to work on practical AI systems, enterprise data, agents, retrieval, workflow automation, and context graphs. You will help connect to client systems, process messy real-world data, build prototypes, and turn business problems into working software.
 
 
 The work is hands-on and client-facing:
 
 
 <ul>
 <li>
 Understand operational workflows and convert them into technical artifacts
 </li>
 <li>
 Connect to real enterprise systems and data sources
 </li>
 <li>
 Build context-aware AI agents, retrieval systems, and automation prototypes
 </li>
 <li>
 Help move the best prototypes toward reliable production deployments
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Build context graphs.
 
 Help ingest, clean, structure, and connect data from enterprise systems into context graph. This may include structured databases, PDFs, spreadsheets, tickets, CRM data, analytics events, Slack or Teams exports, meeting transcripts, operational workflows, and other internal knowledge sources.
 
 
 
 Develop AI and agentic workflows.
 
 Build AI pipelines and agent-based systems that can reason over enterprise context, identify patterns, surface workflow gaps, and suggest or trigger automations. This may involve LLMs, retrieval systems, structured extraction, tool use, LangGraph-style workflows, and agent harnesses.
 
 
 
 Connect to enterprise systems
 
 . Integrate with client infrastructure such as databases, APIs, cloud storage, document repositories, analytics tools, ticketing systems, and internal applications.
 
 
 
 Prototype automation opportunities.
 
 Rapidly build proof-of-concepts that show how AI can improve a client's operations - for example, process documentation, workflow discovery, incident management, document extraction, customer journey analysis, or operational decision support.
 
 
 
 Turn messy business problems into software.
 
 Work with senior engineers and business stakeholders to translate ambiguous operational problems into technical designs, data models, prompts, pipelines, and deployed applications.
 
 
 
 Support production deployments.
 
 Help build reliable, maintainable systems that can run in production environments, including client cloud environments when needed.
 
 
 
 Ideal Candidate
 
 
 
 We are looking for a strong junior software engineer who is excited about applied AI and wants to build real systems, not just experiments.
 
 
 You do not need to be an expert in every area below, but you should be curious, technical, and comfortable learning quickly.
 
 
 
 Technical Background
 
 
 
 <ul>
 <li>
 Strong Python fundamentals
 </li>
 <li>
 Basic backend development experience
 </li>
 <li>
 Familiarity with APIs, databases, and cloud services
 </li>
 <li>
 Interest in LLMs, agents, retrieval, structured outputs, and tool-calling
 </li>
 <li>
 Familiarity with data pipelines and messy real-world datasets
 </li>
 <li>
 Experience with FastAPI, LangChain, LangGraph, vector databases, document processing, or knowledge graphs is a plus
 </li>
 <li>
 AWS experience is a plus
 </li>
 <li>
 Experience with enterprise data, analytics, or workflow automation is a strong plus
 
 
 </li>
 </ul>
 
 What Makes Someone Successful In This Role
 
 
 
 <ul>
 <li>
 You like figuring out how businesses actually operate
 </li>
 <li>
 You are comfortable working with incomplete, messy, or poorly documented data
 </li>
 <li>
 You can move quickly from vague requirements to a working prototype
 </li>
 <li>
 You care about building useful systems, not just impressive demos
 </li>
 <li>
 You communicate clearly with both engineers and non-technical stakeholders
 </li>
 <li>
 You are curious about how AI agents can interact with real tools, data, and workflows
 </li>
 <li>
 You want to learn how to deploy AI into real enterprise environments
 
 
 </li>
 </ul>
 
 Why This Role Is Interesting
 
 
 
 You will work on the frontier of practical enterprise AI: connecting AI agents to real company context and using that context to discover and automate high-value workflows.
 
 
 This is a hands-on engineering role for someone who wants to grow into building production-grade AI systems across data, agents, infrastructure, and enterprise software
</div>

Forward Deployed AI Engineer

TechLabs London

<div>
 
 About TechLabs London:
 
 
 
 At TechLabs London, we build cutting-edge digital products that power smarter, more connected organizations. Our flagship solution is transforming housing management with modern cloud technology, intuitive design, and seamless integration. We are now embedding
 
 AI and intelligent automation
 
 across our platforms &mdash; and this role is at the center of that mission. We&rsquo;re looking for a driven and creative
 
 AI Engineer
 
 to lead this charge with us, to deliver production-ready AI features, predictive analytics, and computer vision tools that unlock real business value.
 
 
 
 Job Purpose:
 
 As an AI Engineer you&rsquo;ll be responsible for the development, deployment, and optimisation of advanced AI and ML capabilities within TechLabs London. You will collaborate with cross-functional teams to embed intelligent solutions into our existing product suite and shape the next generation of AI-powered features across our platforms. This role is perfect for someone who&rsquo;s passionate about building practical AI solutions and wants to see their work improve lives, save time, and power decisions. You&rsquo;ll help the business translate complex challenges into intelligent, scalable solutions.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Design and build end-to-end AI pipelines across use cases such as predictive modelling, NLP, computer vision, and conversational AI.
 </li>
 <li>
 Design, develop and deploy conversational AI solutions using LLMs and agentic frameworks (e.g. LangChain, LangGraph), including RAG pipelines, intent classification, entity extraction, and multi-turn dialogue management.
 </li>
 <li>
 Apply computer vision to extract intelligence from images and videos for detection, classification, and automation.
 </li>
 <li>
 Develop time-series models that analyze behavior and generate predictive.
 </li>
 <li>
 Experiment with foundational models and fine-tune them for specific tasks relevant to our domain.
 </li>
 <li>
 Integrate models into production by working with our developers to deploy solutions into our products and beyond.
 </li>
 <li>
 Architect and build scalable, secure, and reusable ML APIs, workflows, and pipelines using modern MLOps practices and containerisation (Docker).
 </li>
 <li>
 Translate business problems into data-driven solutions, working closely with product, customer success, and engineering teams.
 </li>
 <li>
 Champion AI-first thinking across the company, supporting POCs, internal tooling, and customer-facing features.
 </li>
 <li>
 Collaborate with internal developers, product managers, domain experts, and external stakeholders to ensure solutions are feasible, maintainable, and impactful, as well as to define data strategies and model objectives.
 </li>
 <li>
 Conduct rigorous A/B testing and model evaluation.
 </li>
 <li>
 Support the integration of models into production systems using APIs and microservices.
 </li>
 <li>
 Stay abreast of advancements in AI/ML research and apply relevant breakthroughs to ongoing projects.
 
 
 
 </li>
 </ul>
 
 Skills and Experience:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in information technology, Software Engineering, Computer Science, or related field.
 </li>
 <li>
 Proven experience building and deploying LLM-powered applications, including RAG pipelines and conversational agents.
 </li>
 <li>
 Hands-on experience with LangChain or similar agentic frameworks (LangGraph, AutoGen, or equivalent).
 </li>
 <li>
 Strong proficiency in Python and relevant ML libraries (e.g. pandas, scikit-learn, PyTorch, spaCy, Hugging Face, OpenCV etc.)
 </li>
 <li>
 Experience with cloud platforms &mdash; Azure is our primary platform (preferred); AWS or GCP also considered.
 </li>
 <li>
 Containerization and orchestration: Docker, Docker Compose.
 </li>
 <li>
 Solid understanding of data modelling, feature engineering, and data warehousing concepts.
 </li>
 <li>
 Strong knowledge of SQL and experience with relational and/or vector databases (e.g. pgvector, Pinecone, Weaviate).
 </li>
 <li>
 Proficiency in version control, CI/CD, and model deployment practices.
 </li>
 <li>
 Experience integrating AI models into web or mobile applications is highly valued.
 </li>
 <li>
 Experience with MLOps tools like MLflow, Airflow, DVC.
 </li>
 <li>
 Familiarity with MCP Server (Model Context Protocol) for building tool-augmented AI agents is a plus.
 
 
 
 </li>
 </ul>
 
 Mindset &amp; Soft Skills:
 
 
 
 <ul>
 <li>
 Strong problem-solving and analytical thinking &mdash; able to translate messy real-world data into measurable solutions.
 </li>
 <li>
 Pragmatic and delivery-oriented &mdash; capable of balancing technical innovation with business impact.
 </li>
 <li>
 Communicative and collaborative &mdash; comfortable working across teams and disciplines.
 </li>
 <li>
 Self-driven &mdash; able to manage time, priorities, and project ownership in a fast-moving team.
 </li>
 <li>
 Knowledge of data governance, bias mitigation, and explainable AI techniques.
 </li>
 </ul>
</div>

AI& Data Engineer (Hybrid)

Fimple

<div>
 Fimple is a product company building a cloud-native, highly composable, and extendible platform designed to meet the end-to-end needs of digital, disruptive, and next-generation financial institutions. Our modern, API-native and ecosystem-driven solution, combined with a robust marketplace, enables our clients to stay agile in a rapidly evolving market.
 
 
 We operate in an agile environment with customers across Turkey, GCC, and Europe. Fimple maintains a strong and growing presence in Egypt, alongside our teams in Turkey and a sales office in Dubai, enabling close collaboration in a truly international setup.
 
 
 We are looking for a QC Engineer to join our Delivery team. In this role, you will be responsible for ensuring the quality of our core banking platform through a combination of functional testing, analysis, customer interaction, and automation.
 
 
 
 What Will the Right Person Look Like?
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer engineering, software engineering or a related field
 </li>
 <li>
 1&ndash;2 years of experience in software testing or quality control
 </li>
 <li>
 Strong understanding of software testing principles
 </li>
 <li>
 ISTQB certification is a plus
 </li>
 <li>
 Experience or interest in test automation (Playwright or similar tools)
 </li>
 <li>
 Familiarity with AI tools and their practical usage in daily work
 </li>
 <li>
 Understanding of banking systems is a plus
 </li>
 <li>
 Strong analytical thinking and problem-solving skills
 </li>
 <li>
 Ability to communicate clearly in English (written and spoken)
 </li>
 <li>
 Comfortable working in a fast-paced, agile, and international environment
 </li>
 <li>
 Curious mindset with openness to learning new technologies
 
 
 </li>
 </ul>
 
 What Will You Be Doing?
 
 
 
 <ul>
 <li>
 Collaborate with development teams to understand new features and changes
 </li>
 <li>
 Write and execute functional and regression test cases
 </li>
 <li>
 Take ownership of a banking domain (e.g., loans, accounts, payments)
 </li>
 <li>
 Support UAT and production processes with customers
 </li>
 <li>
 Analyze Jira tickets (bug/support), identify root causes, and coordinate resolutions
 </li>
 <li>
 Communicate effectively with both technical teams and clients
 </li>
 <li>
 Develop and maintain web test automation using Playwright
 </li>
 <li>
 Actively use AI tools to improve testing, analysis, and productivity
 </li>
 </ul>
</div>

QC Engineer (Banking Domain)  
Cairo Residency is Required / Hybrid
Hybrid

Explore 243+ Ai automation engineer light in Cairo this May. Find roles across top companies and apply now to boost your career.

243 ai automation engineer light jobs In Cairo

AI & Automation Engineer, LIGHT

AI & Automation Engineer, LIGHT

DevOps Engineer

Senior Software Quality Engineer

Forward Deployed AI Engineer

AI& Data Engineer (Hybrid)

QC Engineer (Banking Domain) Cairo Residency is Required / Hybrid Hybrid