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callofdutymobileindia · 10 days ago

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How to Choose the Right Artificial Intelligence Course in Dubai for Your Career Goals?

In today’s fast-evolving tech landscape, Artificial Intelligence (AI) is no longer just a buzzword—it's a driving force behind innovation, automation, and digital transformation. From finance and healthcare to aviation and real estate, AI is revolutionizing industries across the globe and Dubai is at the forefront of this change in the Middle East.

With the UAE’s National Artificial Intelligence Strategy 2031 in motion, there’s never been a better time to invest in upskilling. If you're considering an Artificial Intelligence course in Dubai, the options can be overwhelming. The real question is: How do you choose the right course aligned with your career goals?

In this guide, we’ll walk you through everything you need to consider—from your background and aspirations to course content, learning mode, and institute credibility.

Why Take an Artificial Intelligence Course in Dubai?

Dubai is investing heavily in AI to become a global leader in smart governance, digital economy, and innovation. Some compelling reasons to learn AI in Dubai:

High job demand: AI specialists, machine learning engineers, data scientists, and NLP experts are in high demand.

Government support: Initiatives like Smart Dubai and AI Labs are creating an AI-friendly ecosystem.

Global exposure: Dubai’s diverse workforce and tech-savvy infrastructure offer excellent learning and networking opportunities.

Step-by-Step Guide to Choosing the Right AI Course in Dubai

1. Define Your Career Goals Clearly

Before enrolling, ask yourself:

Do I want to become an AI engineer, data scientist, machine learning specialist, or AI product manager?

Am I upskilling in my current job or switching to a completely new field?

Do I need a foundational course, or am I ready for an advanced specialization?

This clarity will help you narrow down courses based on your goals and current skill level.

2. Assess Your Background and Prerequisites

Most AI courses require basic knowledge of:

Mathematics & Statistics

Programming (Python preferred)

Data handling skills (Excel, SQL, etc.)

If you're a beginner, look for AI courses in Dubai that start from scratch or offer a foundation module.

If you have experience, consider courses that skip the basics and dive straight into advanced AI topics like deep learning, reinforcement learning, or generative AI.

3. Compare Course Content & Curriculum

Not all AI courses cover the same material. A good Artificial Intelligence course in Dubai should include:

🔹 Core Modules:

Python Programming for AI

Statistics and Linear Algebra

Machine Learning (Supervised and Unsupervised)

Deep Learning (CNNs, RNNs)

Natural Language Processing (NLP)

🔹 Emerging Trends:

Generative AI (e.g., ChatGPT, DALL·E)

Computer Vision

AI in Cloud (AWS, Azure, GCP)

Responsible AI and Ethics

🔹 Hands-on Projects:

End-to-end AI project using real datasets

Industry case studies

Portfolio-worthy capstone projects

Make sure the curriculum is up-to-date, industry-aligned, and project-focused.

4. Verify Instructor Credentials and Industry Exposure

AI is a complex domain that evolves rapidly. Look for courses that are taught by:

Experienced AI professionals or PhDs

Instructors working in top companies or AI startups

Guest lecturers from the UAE’s tech ecosystem

Also check whether the course includes live mentorship, doubt-clearing sessions, or career counselling.

5. Check for Recognized Certification

After completing the course, your certification should:

Be globally recognized or affiliated with reputable organizations

Boost your resume and credibility

Help in job interviews or visa sponsorships (if you’re an expat)

Some institutes even offer dual certifications or endorsements from platforms like IBM, Microsoft, or Google.

6. Ensure Career Support and Placement Assistance

A course that helps you learn AI is great—but one that helps you get hired is even better. Look for these features:

Dedicated career services

Resume building workshops

Interview prep and mock tests

Job referrals or hiring partner networks

Institutes like Boston Institute of Analytics (BIA) in Dubai offer strong placement support in addition to academic training.

Recommended AI Institute in Dubai: Boston Institute of Analytics

Boston Institute of Analytics (BIA) is one of the most respected names offering AI and Machine Learning courses in Dubai. It stands out for:

Globally recognized AI curriculum

Live classroom sessions and personalized mentorship

Industry-expert faculty

Affordable fee structure with flexible payment plans

Real-world projects and certification

Dedicated career support and placement services

Whether you're a fresher, working professional, or entrepreneur, BIA's Artificial Intelligence Course in Dubai equips you with job-ready AI skills and helps you stay ahead of the curve.

Final Thoughts

Choosing the right Artificial Intelligence course in Dubai isn’t just about picking the most expensive program or the most popular brand. It’s about finding the perfect match between your career goals, budget, skill level, and learning style.

Here’s a quick checklist before you enroll:

✅ Clear career objective ✅ Beginner-friendly or advanced curriculum ✅ Live or hybrid learning formats ✅ Project-based, hands-on training ✅ Valid certification and career support ✅ Positive reviews and alumni outcomes

With the right course, you’re not just learning AI—you’re investing in a future-proof career. And in a global city like Dubai, the opportunities are limitless if you have the right skills and credentials.

#Best Data Science Courses in Dubai #Artificial Intelligence Course in Dubai #Data Scientist Course in Dubai #Machine Learning Course in Dubai

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praveennareshit · 1 month ago

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Where to learn cloud computing for free ?

💡 Where to Learn Cloud Computing for Free? Your First Steps in 2025

So you’ve heard about cloud computing. Maybe you’ve seen the job titles—Cloud Engineer, DevOps Specialist, AWS Associate—or heard stories of people getting hired after just a few months of learning.

Naturally, you wonder: "Can I learn cloud computing for free?"

Yes, you can. But you need to know where to look, and what free learning can (and can’t) do for your career.

☁️ What Can You Learn for Free?

Free cloud resources help you understand:

What cloud computing is

How AWS, Azure, or GCP platforms work

Basic terminology: IaaS, SaaS, EC2, S3, VPC, IAM

Free-tier services (you can try cloud tools without being charged)

Entry-level certification concepts

�� Best Places to Learn Cloud for Free (Legit Sources)

✅ AWS Free Training & AWS Skill Builder

📍 https://aws.amazon.com/training

Learn cloud basics with self-paced videos

Good for AWS Cloud Practitioner prep

Access real AWS Console via the free tier

✅ Microsoft Learn – Azure

📍 https://learn.microsoft.com/en-us/training

Offers free Azure paths for beginners

Gamified learning experience

Ideal for preparing for AZ-900

✅ Google Cloud Skills Boost

📍 https://cloud.google.com/training

Interactive quests and labs

Learn Compute Engine, IAM, BigQuery

Some credits may be needed for advanced labs

✅ YouTube Channels

FreeCodeCamp: Full cloud crash courses

Simplilearn, Edureka, NareshIT: Basic tutorials

AWS, Azure official channels: Real demos

✅ GitHub Repos & Blogs

Open-source lab guides

Resume projects (e.g., deploy a website on AWS)

Real-world practice material

⚠️ But Wait—Here’s What Free Learning Misses

While free content is great to start, most learners eventually hit a wall:

❌ No structured syllabus

❌ No mentor to answer questions

❌ No feedback on real projects

❌ No resume guidance or placement support

❌ Certification confusion (what to take, when, why?)

That’s where formal, hands-on training can make the difference—especially if you want to get hired.

🎓 Want to Learn Faster, Smarter? Try NareshIT’s Cloud Courses

At NareshIT, we’ve helped over 100,000 learners start their cloud journey—with or without a tech background.

We bridge the gap between free concepts and job-ready skills.

🔹 AWS Cloud Beginner Program

Duration: 60 Days

Covers EC2, IAM, S3, Lambda

Includes: AWS Cloud Practitioner & Associate exam prep

Ideal For: Freshers, support engineers, and non-coders

🔹 Azure Fundamentals Course

Duration: 45 Days

Learn VMs, Azure AD, Blob Storage, and DevOps basics

Prepares you for AZ-900 and AZ-104 certifications

Best For: IT admins and .NET developers

🔹 Google Cloud (GCP) Basics

Duration: 30 Days

Practice labs + GCP Associate Cloud Engineer training

Perfect for: Python devs, data learners, AI enthusiasts

📅 View all cloud training batches at NareshIT

👣 Final Words: Start Free. Scale Smart.

If you’re serious about cloud, there’s no shame in starting with free videos or cloud tutorials. That’s how many great engineers begin.

But when you’re ready to:

Work on real projects

Earn certifications

Prepare for interviews

Get career guidance

Then it’s time to consider a guided course like the ones at NareshIT.

📌 Explore new batches →

#cloudcomputing #cloudengineer #clouddevelopment #aws #azure #devops #technology #cloudsecurity

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enoumen · 3 years ago

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GCP Professional Machine Learning Engineer Quizzes, Practice Exams: Framing, Architecting, Designing, Developing ML Problems & Solutions ML Jobs Interview Q&A ios: https://apps.apple.com/ca/app/gcp-machine-learning-eng-pro/id1611101916 Windows: https://www.microsoft.com/en-ca/p/gcpprofmachinelearningengineer/9nf14pr19bx5 Use this App to learn about Machine Learning on GCP and prepare for the GCP Professional Machine Learning Engineer. GCP Professional Machine Learning Engineer validates expertise in building, training, tuning, and deploying machine learning (ML) models on GCP. The App provides hundreds of quizzes and practice exams about: - Machine Learning Operation on GCP - Framing ML problems, - Architecting ML solutions, - Designing data preparation and processing systems, - Developing ML models, - Modelling - Data Engineering - Computer Vision, - Exploratory Data Analysis, - ML implementation & Operations - Machine Learning Basics Questions and Answers - Machine Learning Advanced Questions and Answers - Scorecard - Countdown timer - Machine Learning Cheat Sheets - Machine Learning Interview Questions and Answers - Machine Learning Latest News The App covers Machine Learning Basics and Advanced topics including: Monitoring, optimizing, and maintaining ML solutions, Automating and orchestrating ML pipelines, NLP, Modelling, Etc. #GCPML #MachineLEarning #GCPProfessionalMachineLearningEngineer #GoogleMl #CloudMl #NLP #AI #GCpAI https://www.instagram.com/p/Ca8bZVMJUos/?utm_medium=tumblr

#gcpml #machinelearning #gcpprofessionalmachinelearningengineer #googleml #cloudml #nlp #ai #gcpai

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anytutor37-com · 5 years ago

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Azure Full Course - Learn Microsoft Azure in 8 Hours | Azure Tutorial For Beginners | Edureka

** Azure Training - https://www.edureka.co/microsoft-certified-azure-solution-architect-certification-training ** This Edureka Azure Full Course video will help you understand and learn Azure & its services in detail. This Azure Tutorial is ideal for both beginners as well as professionals who want to master Azure services. Below are the topics covered in this Azure Tutorial for Beginners video: 00:00 Introduction 3:02 Why Cloud? 3:07 Before Cloud Computing 6:17 What is Cloud? 8:07 What is Cloud Computing? 8:42 Service Models 9:32 SaaS 10:17 PaaS 10:37 IaaS 11:17 Deployment Models 11:27 Public Cloud 11:57 Private Cloud 12:07 Hybrid Cloud 12:42 Cloud Providers 25:12 Azure Fundamentals 25:17 Getting Started with Azure 27:42 What is Microsoft Azure? 28:17 Use-case 30:02 How will we implement this? 34:02 Azure Components 34:12 App Service 34:22 Compute Domain 40:57 Blob Storage 41:22 Storage Domain 46:16 MySQL for Azure 46:49 Auto Scaling & Load Balancing 49:43 How to launch services in Azure? 1:04:53 Demo 1:23:08 Azure Pricing 1:28:33 Storage Domain 1:29:33 Why Storage? 1:33:48 Storage vs Database 1:34:58 What is Azure Storage? 1:41:38 Components of Azure Storage 2:12:35 Network Domain 2:12:40 Virtual Networks 2:13:35 What is Virtual Machine? 2:14:35 Why Virtual Networks? 2:15:35 What is Virtual Network? 2:16:50 What are Azure Subnet? 2:18:35 Network Security Groups 2:19:05 Virtual Network Architecture 2:20:00 Demo 3:08:24 Access Management 3:08:34 Azure Active Directory 3:09:14 What is Azure Active Directory? 3:12:26 Windows AD vs Azure AD 3:14:11 Service Audience 3:15:56 Azure Active Directory Editions 3:16:31 Azure Active Directory Tenants 3:36:06 Azure DevOps 3:36:26 What is DevOps? 3:42:21 Components of Azure DevOps 3:48:11 Azure Boards 4:20:16 Azure Data Factory 4:21:21 Why Data Factory? 4:23:06 What is Data Factory? 4:25:51 Data Factory Concepts 4:27:26 What is Data Lake? 4:29:01 Data Lake Concepts 4:33:31 Data Lake vs Data Warehouse 4:36:46 Demo: Move Data From SQL DB to Blog Storage 4:59:16 Important Services & Pointers 4:59:26 Azure Machine Learning 5:01:26 Machine Learning 5:06:01 Machine Learning Algorithms 5:08:36 Various Processes in ML Lifecycle 5:11:41 Microsoft Azure ML Studio 5:34:56 Azure IoT 5:35:46 What is IoT? 5:41:11 IoT on Azure 5:44:56 Azure IoT Components 5:57:31 Azure BoT Service 6:00:31 What are ChatBots? 6:04:36 Need for Chatbots 6:07:51 Demo: Creating a ChatBot for Facebook Messenger 6:41:06 AWS vs Azure vs GCP 6:51:36 Security 6:52:16 Integration 6:53:06 Analytics & ML 6:53:51 DevOps 6:54:26 Hybrid Capabilities 6:55:01 PaaS Offerings 6:55:26 Learning Curve 6:55:46 Scalability 6:56:26 Cost Efficient 6:57:11 The Final View 6:59:01 Cloud Careers 6:59:11 Azure Interview Questions 7:36:06 Cloud Engineer Jobs, Salary, Skills & Responsibilities 7:36:41 Cloud Engineer Job & Salary Trends 7:46:51 Cloud Engineer Job Skills & Description 7:51:51 Cloud Engineer Responsibilities -------------------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ---------------------------------------------------------------------------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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tak4hir0 · 6 years ago

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It starts with someone posting an AWS press release in the company chat. “AWS Announces FooBar,” the headline reads. The announcement skirts around technical details, as usual, but contains a worrying amount of buzzwords that overlap with the company’s product. Somebody responds with a grimace emoji 😬. Others reply with all the ways AWS FooBar is totally not like our product and, anyway, ours is better, and, and… The flurry of replies betrays their true collective emotion: We’re screwed. They’re right to be worried. As a marketing consultant to enterprise software startups for the past six years, I’ve helped companies navigate and succeed in this scenario at least eight times.[1] In this article I explain why every software startup should be prepared for this scenario, why the initial panic is justified, and how to position products against alternatives from “Big Cloud” (AWS, Azure, GCP). Every Software Startup Should Be Prepared to Compete Against AWS, Azure, and GCP Even if you’re not competing with Big Cloud today, there’s a good chance you will soon. This is especially true if your product is in the serverless, stream processing, machine learning, containerization, IoT, data warehousing, or batch processing space. Those are the fastest growing cloud services—according to a survey from Rightscale—and Big Cloud companies know it. Big Cloud companies earn the bulk of their revenues from metered billing of storage, compute, and streaming. Having turned those infrastructure workloads into commodities, the Big Cloud companies are in a race to provide differentiated products higher in the stack just to bring more customers onto their infrastructure. That is evident in the sheer size of their product portfolios and pace of product releases: AWS has 182 products and made 83 major product announcements (launches or major releases) in 2018.[2] You Should Worry When Big Cloud Launches a Similar Product There is a tendency, upon learning of a Big Cloud intrusion, to bury our heads. Internal emails will include explanations for why the Big Cloud product “is not really competitive,” “is not as good as ours,” and “can only take a small piece of the market.” Maybe those things turn true, but there are good reasons to at least take the competition seriously: 1. Resource Imbalance Big Cloud companies can win by brute force: Pouring obscene amounts of resources into engineering, marketing, and sales until they outrun or outlast the competition. It won’t be enough to have a better product by a smidgen, or to have a small head start in the market. 2. Complicated Relationship Startups participating in Big Cloud partner programs, such as the AWS Partner Network, will find themselves sharing sensitive information and valuable resources with the competition. For them, leaving the program would mean relinquishing a potentially significant acquisition channel. Meanwhile, Big Cloud wouldn’t flinch at losing a startup partner, and therefore has no incentive to be prudent with the information it obtains. 3. Broad Reach and Influence AWS can get on stage and influence a thousand people, or send an email and influence a hundred thousand, or play a TV commercial and influence millions. Using their broad reach and brand recognition, Big Cloud can influence how people perceive the market and make their decisions. 4. Captive Audience Even better than a reachable audience is a captive audience. Big Cloud companies have millions of users, already running on their platforms and familiar with their products. They can reach this audience to upsell and cross-sell products in a few clicks. 5. Pricing The objective for most Big Cloud products is not to make profit, but to bring customers onto the platform and increase infrastructure usage (compute, storage, streaming). Therefore the products can be users as loss leaders: Priced at very low or no cost, provided they drive increased infrastructure usage. For startups, at best this eliminates the option to compete on price, at worst it forces them to lower prices with no way to make up for it. 6. Easy Access Engineers at companies already running on AWS can buy, deploy, and integrate an AWS product before their coffee cools. Metered billing means there are no upfront costs or negotiations. Being on the same platform means seamless integration between tools and services. 7. Early decision In the past, decision makers had to choose whether to build a solution in-house or purchase software from a vendor. Today, the low prices, easy access, and brainshare of Big Cloud offerings create a new option for decision makers: Use what their cloud platform is offering. It used to be “buy vs build.” Now it’s “buy vs build vs big cloud.” For software startups, this means they can be ruled out even earlier in the buying process, before any conversation, evaluation, or feature comparison takes place. How to Win Against Big Cloud Prepare Attend trade shows, seek out insiders who might tip you off about looming competition, and generally keep an ear to the ground. Advance warning will allow you to dredge a wider moat, prepare a response, and avoid company-wide panic when the press release hits. Having a pre-emptive strategy for competing against Big Cloud will make it possible to ride the initial wave of hype following their announcement, leveraging their campaign to bring attention to your own product, and pulling away from other startups who will be caught by surprise. With the right strategy and execution, the launch of a competitive product from Big Cloud could be turned into a positive inflection point for the startup and its market. Even if you are not competing against Big Cloud now, good preparation will improve reaction time and chances of succeeding when the moment comes. If your product even remotely encourages more use of cloud compute, storage, or streaming, then you should prepare. Support Multi-Cloud According to the same survey by Rightscale, 84% of enterprise organizations have applications and workflows scattered across on-prem, private cloud, and public cloud environments. If you are “the #1 solution for X on AWS,” and AWS launches a solution for X, you become a distant second choice. If your product works across a variety of environments, then it will remain a viable—and probably better—option for buyers that want to solve an organization-wide problem. Those buyers will need a solution that works across their entire infrastructure, not just the part on AWS. Support for multi-cloud and hybrid environments is one of the most common reasons I hear from decision makers for why they bought software instead of using the cloud offering. Multi-cloud and hybrid-environment support could be a decisive advantage over Big Cloud offerings. And, unlike a small lead in features, this advantage will last a while: Big Cloud companies have little incentive to make products for other platforms. With options like Kubernetes and Gravity, adding that capability to products may not require a monumental engineering effort. Think Twice Before Open-Sourcing While it helps with awareness and credibility, open-sourcing products in whole or in part lowers the barrier to entry for competitors. For any new and sufficiently popular open-source product X, it is trivial for Big Cloud to introduce a “Managed X” offering, as AWS did with Elasticsearch, or to pair it with their security products and package it as “X for Enterprise,” as AWS did with MongoDB and as Google did with Kubernetes. (The Kubernetes story has a few fun twists in it: First, the company Docker released an open-source containerization product. By the time they launched a paid container management service, Google already developed and open-sourced their own container management solution, Kubernetes, which won the market. Then, after Docker released an enterprise solution for managed containers, Google beat Docker once again with the launch of Google Kubernetes Engine.) For example, when AWS launched a “Fully managed, scalable, and secure” packaging of the open-source software Elasticsearch, it led the makers of that software to admit: “… Amazon competes with us for potential customers, and while Amazon cannot provide our proprietary software, the pricing of Amazon’s offerings may limit our ability to adjust the price of our products.” The questionable benefits of open-core business models, combined with the vulnerability it opens to competition from Big Cloud companies—who are not ashamed of taking advantage—is why I advise companies to guard their product and not go open-source, or to limit their vulnerability if they already open-sourced, as Confluent did by changing their licensing when AWS pulled the same maneuver with Kafka, the open-source software from Confluent. Position Against the Category, Not the Product Now that companies decide between “build vs buy vs big cloud” before doing side-by-side comparisons of products, startups must position their product as a better alternative or complement to the entire “big cloud” category of solutions. Don’t talk about who has the better features. First, given the engineering resources available to Big Cloud companies, any feature advantage will be short-lived. Second, buyers make feature comparisons much later in the buying process, after ruling out the majority of options based on their perception—not features—of those products. So why is your product better than Big Cloud, despite the (likely) higher cost and time to deploy? Here are common answers I have found from my interviews with buyers, that may or may not apply to your product: Works Anywhere with Anything “Our product deploys, runs, and integrates with applications on any infrastructure. Organizations running applications hybrid or multi-cloud environments can use the product without restrictions and without consolidating to one cloud provider.” Self-Service for Non-Technical Users “Products from Big Cloud providers often serve the users closest to infrastructure work, such as engineers, operators, architects, developers. Our product lets non-technical users such as […] do their work without being blocked by or burdening technical teams.” End-to-End Solution “Our product is an end-to-end solution that does not require engineering work to glue parts and other systems together. Big Cloud products act more like building blocks that work well with other parts of their platform, but are not that useful or even usable on their own.” Purpose-Built “Our product was made—and continues to be developed—to solve the unique needs of your industry. It integrates seamlessly with people, workflows, tools, and systems you already have, such as […].” Expert Partners “In addition to documentation and examples relevant to your use cases, we provide expert support and consultation to all customers, regardless of their size.” Customer-Driven Development “We are laser-focused on making the best product for […], constantly making improvements based on input and emerging needs of people like you.” If you’re still unsure how to explain your advantage over Big Cloud products, ask the buyers who chose you over AWS, Azure, or GCP, like I did for Gravitational and for Netlify. After developing new positioning to compete against Big Cloud, turn it into new or updated messaging, align the company on that messaging, and bring it to market through your sales and marketing channels. Conclusion The entry of Big Cloud is not always a death knell, but it’s serious. Startups that acknowledge the threat from Big Cloud companies, prepare accordingly, and react with the right strategy and sense of urgency could not only survive but thrive. Maybe even long enough to be acquired by one. [1] An incomplete list: I was consulting FoundationDB when AWS launched Aurora; Scalyr when AWS launched its Elasticsearch service (often used for searching through logs); Gravitational when Google launched GKE; Domino Data Lab when AWS launched Sagemaker; Etleap when AWS launched Glue; Nexla when Google acquired Alooma and as AWS launched AWS Lake Formation; Netlify when Google acquired Firebase and when GitHub (owned by Microsoft) launched Actions. In one case I saw things from the other side: When the startup Particle launched their IoT solutions, I was consulting AT&T on launching their own IoT platform and marketplace… True to form, AWS also launched an IoT platform that year. [2] Product counts are approximate, and do not include general business product groups such as G Suite or Office 365. Sources: 1, 2, 3, 4, 5, 6, 7, 8. ◼ PS - Liked this article? I write one every month or so, covering lessons learned on B2B startup growth. Don't miss the next one:

#Greg Kogan

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jobswzayef · 5 years ago

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Technical Architect Remote 100 000 year USD

Technical Architect Remote 100 000 year USD Remote work is quickly becoming the default option for high tech jobs. Crossover is the platform for top paying full time long term remote work and now is a great time to get onboard. We are growing rapidly across nearly 50 different job positions. This listing is for our Technical Product Manager position but we have found great applicants often have a current title of Technical Architect or similar so don’t be confused about that difference we are glad you found us. Hit “Apply” to learn more about this exciting opportunity. Are you the best architect on your team stuck working on the same codebase for quarters or even years at a time? Do you have 1 000 ideas about how you could make the applications you’ve inherited simpler and more maintainable if only your stakeholders would give you the time you need to do things right? Do you enjoy learning and using the latest cloud services? If so you'll love our view of Technical Product Management. Our TPMs have strong engineering backgrounds because they are focused on different things than your typical PM. Our TPMs are focused on...

Designing better and simpler technical solutions not managing a long feature backlog.< li>

Improving core data structures and algorithms not the UI UX layer< li>

Maximizing the use of disruptive technology not low value and undifferentiated code < li>< ul>Key responsibilities

Making Technical Decisions. Identifying the Important outcomes Evaluating alternatives Looking for the best simplest pattern deciding how to apply existing patterns to a given problem adding detail to P2 decisions< li>

Learning Important Context. Interviewing Product Architects Reading Docs Using Products Learning new APIs or Services Reading Code Evaluating Technical Patterns< li>

Reviewing Content. Reviewing deliverables created by Engineers. Deciding whether to Approve or Reject with feedback .< li>

Writing. Creating milestone specs and decisions using diagrams to communicate technical decisions. < li>< ul>Candidate requirements

A university degree including the study of data structures algorithms and computing fundamentals.< li>

At least 2 years of experience writing object oriented production code for a commercial software company.< li>

At least 2 years of experience making important architecture and design decisions such as data domain modeling application of design patterns and design using third party components.< li>

Some experience designing for cloud computing paradigms such as Amazon Web Services Azure or Google Cloud Platform .< li>

The ability to simplify complex ideas and communicate them with clear logical thinking. < li>< ul>Nice to have

Experience rebuilding redesigning existing products on top of entirely new cloud services for example all the AWS services beyond EC2 and S3 .< li>

Experience writing technical architecture documents< li>

AWS Azure GCP Certifications < li>< ul>What you will be doing As a Crossover TPM you will have a long term role on a team that makes the important architecture decisions across a steady stream of product releases that are fueled by Trilogy's growing portfolio of 100s of enterprise software applications. Our TPMs use the latest cloud patterns and services to rearchitect many applications each year. Most people are lucky to have the opportunity to create foundational technical direction a few times in their careers. Because of our virtually endless supply of modernization and cloud rebuild projects our TPMs make these decisions every week. Day to day TPMs

Turn high level technical specs into detailed designs that engineers can execute on< li>

Uphold high standards on fundamental data structures algorithms and architectural best practices< li>

Define the acceptance criteria to measure engineering deliverables against < li>< ul>There is so much to cover for this exciting role and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! What to expect next

You will receive an email with a link to start your self paced online job application.< li>

Our hiring platform will guide you through a series of online “screening” assessments to check for basic job fit job related skills and finally a few real world job specific assignments.< li>

You will be paired up with one of our recruiting specialists who can answer questions you might have about the process role or company and help you get to the final interview step. < li>< ul>Important! If you do not receive an email from us

First emails may take up to 15 minutes to send refresh and check again.< li>

Second check your spam and junk folders for an email from Crossover.com mark as “Not Spam” since you will receive other emails as well.< li>

Third we will send to whatever email account you indicated on the Apply form by default that is the email address you use as your LinkedIn username and it might be different than the one you have already checked.< li>

If all else fails just visit https jobs.crossover.com directly search for this job and click “Apply”. You will be prompted to reset your password if you already applied using LinkedIn EasyApply. < li>< ul>Crossover Job Code LJ 3335 SA Riyadh TechnicalArchi * راتب مجزي جداً. * مكافأت و حوافز متنوعة. * توفير سكن مؤثث أو بدل سكن. * أنتقالات أو توفير بدل عنها. * توفير تذاكر السفر لمن يشغل الوظيفة و عائلته. * نسبة من الأرباح الربع سنوية. * أجازات سنوية مدفوعة الراتب بالكامل. * مسار وظيفي واضح للترقيات. * بيئة عمل محفزة و مناسبة لحالة الموظف. * تأمين طبي للموظيف و عائلته. * تأمينات أجتماعية. التقدم و التواصل مباشرة دون و سطاء عند توافر الألتزام و الجدية التامة و المؤهلات المطلوبة علي: [email protected]

#وظيفة #وظائف_شاغرة #وظائف_خالية #وظائف_كوم #وظيفة_كوم #السعودية #الكويت #الأمارات #عمان #ا

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