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Software Engineering

Software Engineer, iTunes Big Data Social - IoT BigData Jobs


The iTunes big data engineering team is looking for talented server-side engineers to build and enhance social features such as those underpinning Apple Music. This is your opportunity to contribute to key Apple services built using massively scaled systems, on a team located in San Francisco and working closely with Cupertino and London. Key Qualifications Minimum of 5 years professional software engineering experience. Proficiency in building Node.js applications. Experience with building RESTful APIs. Experience with a NoSQL solution, document store, or key-value store (e.g. Cassandra, Redis, MongoDB, Couchbase). Comfortable with Linux command line tools and basic shell scripting. Description Our team is responsible for architecting and delivering services such as those central to Apple Music Connect that allow users and artists to interact with each other. To build these features, we create server-side applications that employ a combination of microservices, message-passing, caching layers, and distributed databases. We serve our data over cleanly designed RESTful HTTP endpoints used by multiple client platforms making a massive number of requests per second at millisecond response times. This is a great opportunity to join a small but growing team of motivated engineers, with wide responsibility and high-profile feature ownership. Whether you’re interested in architecture, data modeling, plumbing data pipelines, or designing endpoints, there are numerous possibilities for building new features from scratch and enhancing the existing infrastructure. Education Education: BS or MS in Computer Science, or equivalent experience Additional Requirements Experience with building highly scalable services using a microservices architecture. Experience with message-based architectures using Kafka or other another message broker. Experience with Agile software development methodologies including Scrum and TDD (test-driven development). Ability to collaborate with cross-functional teams. Familiarity or experience with Java or another object-oriented programming language. Experience with Git.

Managing the Organized Chaos That Is Software Development


Disclaimer: This article is written mostly by GPT-3 given the first paragraph as a prompt; a few edits were made for style and clarity. Complex software projects require a level of discipline to ensure meeting deadlines and hitting milestones on time; however, software development is a creative process as well that calls for flexibility and leeway for experimentation. Software organizations need to strike that balance well to stay innovative and effective at the same time -- you may call it organized chaos. Software development projects can be chaotic, especially if you don't know what to do. If you ask any software developer about their experience, you'll likely hear one of two things: "I have no management skills," or "I don't have enough time to manage my team."

Solving the AIOps, DevOps, And ITSM Conundrum -


Quickly shifting to remote work has enterprises looking to meet the ops needs of a suddenly distributed team, and there are open source options to get them there. The recent mad rush to scale to remote work may prove to be a key chapter in DevOps and AIOps evolution. This need for rapid, widescale change is creating a real conundrum concerning AIOps, DevOps, and ITSM, as organizations seek the best monitoring and incident response solution for their now distributed enterprises. The key question both the DevOps and IT service management (ITSM) communities need to answer is how quickly they can pivot and adapt to increasing demands for operational intelligence. Artificial intelligence for IT Operations (AIOps) brings together artificial intelligence (AI), analytics, and machine learning (ML) to automate the identification and remediation of IT operations issues.

10 Predictions On Software Development Trends Of 2022


What are the trends in software development over the second half of 2020? This is like no other year. The prevailing issue has turned the world upside down, pushing companies to take on new technology's challenges and analyze their digital strategies. Digital has become the principal (and, in some cases, only) channel of customer interaction and engagement. Enterprises with the digital projects designed to be implemented within the next one to three years need to speed up their initiatives.

Software developers: How plans to automate coding could mean big changes ahead


For the vast majority of humans, writing code is akin to learning a new language – but researchers from Intel and MIT are on a mission to change that. And the solution they are coming up with is to build code… that can code. Called machine programming, the field that the researchers are looking at is concerned with automating software development. And the team has just revealed a new tool that takes developers one step closer to the prospect of, one day, having machines that can program themselves. MISIM (Machine Inferred code Similarity), the new technology invented by Intel and MIT's labs, effectively studies snippets of code to understand what a piece of software intends to do.

Top 5 Mobile App Development Trends to Watch Out for in 2020


Mobile Development has become one of the most critical aspects of many companies. This is due to the acquisition of a more organic base of clients. Without a mobile-optimized solution, a company could face the question of lagging behind its competitors. Given that revenue from mobile apps' development has reached a new peak, people are following the trend in app development. Both the users and the developers follow the path of making life more comfortable.

How AI and ML are the Next Evolutionary Step for DevOps


DevOps and Machine Learning share a powerful alliance with related capabilities like predictive analysis, algorithmic IT operations, Operations Analytics, and AI. Introduction of Machine Learning into DevOps has brought benefits such as checking highly complex data sets. Detect patterns and antipatterns, uncover new ideas, repeat and refine queries with the speed and perfection. For example, delivery processes can be tracked with various DevOps tools, these tools produce a lot of data and any kind of error in this data can be detected by the application of Machine Learning. Large code volume, slow-release rate, and long built times are some of the issues that can be put in check using Machine Learning.

How does AI help in software testing?


The foundations of every great software that we know today lay in its testing. The software testing industry is a big industry whose fundamental purpose is nothing but one- help produce the best software in the market. While there's not much that it does in terms of the development, there's a lot that that testing shares as its feedback and passes on to the development. If you're wondering whether software testing is a whole new field of itself separate from the fundamental development, you're probably mistaken. While it has an entirely new area to it and further sub-fields, it often goes in tandem with the software development procedure.

How to scale automation in DevOps environments


The telecom giant CenturyLink created a federated program to scale automation efforts, where one dedicated team curated standards and best practices that were then rolled out across the company. CenturyLink -- a facilities-based communications company with 40,000 full-time employees, based out of Monroe, La. -- wanted to achieve automation at scale and blend the best characteristics of application development, scripting, and robotic process automation (RPA) tooling, said Troy Ferrence, senior manager of automation solutions architecture at CenturyLink. For the past several years, Ferrence's team has focused on scripting and application development, but its efforts accelerated when CenturyLink introduced RPA software that used the UiPath platform. CenturyLink expanded its work to more than 19 teams dedicated to this project, referred to as center of excellence teams, in the last year and developed over a thousand different automations. "We have a lot of legacy applications where we don't have any type of interface or availability for enhancement which are perfect candidates for RPA," Ferrence said.