BENGALURU: Fresh IT graduates having specialized skills in areas such as Artificial Intelligence, Machine Learning, and full-stack development are in top demand. Firms are offering annual salary between Rs. 8.2 lakh and Rs. 10.2 lakh for such talent.
Niche skills in AI/ML, cybersecurity, and cloud computing are commanding a premium compensation for freshers, said Ramesh Alluri Reddy, CEO of TeamLease Degree Apprenticeship. Such candidates can quote up to 20-30% higher starting salary due to the high demand and limited supply in this critical area.
The compensation offered to a fresher will be in the range from Rs. 3.5 lakh to Rs. 6 lakh per annum in the IT services segment. This, again depends on the role and the organization. IT product companies, however, may offer freshers who are specialized in a skill, 50-80 per cent more salary.
Recent report by TeamLease Digital revealed that AWS and Microsoft Azure skills are highly in demand. Xpheno, a specialist staffing firm, informed that IT companies are paying salary in the range of Rs. 3.6- Rs. 4.5 lakh for engineering freshers and Rs. 2.2- Rs. 2.8 lakh for non-engineering freshers.
It is estimated that 82% of freshers in the IT services sector get less than Rs. 5 lakh per annum, 12% between Rs. 5 lakh to Rs. 7.5 lakh, and 7% above Rs. 7.5 lakh. Non-tech sectors, such as BFSI, manufacturing, and pharma, pay Rs. 2.5 lakh or less per annum to nearly 48% of fresh graduates, while 38% fall in the Rs. 2.5 lakh to Rs. 5 lakh category.
Krishna Gautam, Business Head, Xpheno, adds, "Skill-based outlier packages range from Rs. 6 lakh to Rs. 12 lakh based on the tech stack, specialisation, unique project experiences, and performance on internal skill grading systems.".
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Cloud computing involves using remote servers to store data and run applications, rather than relying on local, on-premise systems. Careers in cloud computing are diverse, ranging from roles like cloud architects to cloud security engineers.
This guide is tailored for companies that use cloud services, such as hospitals or banks, rather than providers like Amazon, Google, or Microsoft. These big tech companies also offer various certifications that are highly regarded in the industry.
Understanding Cloud Computing Roles
To get started in cloud computing, it's helpful to break down the field into its key technical areas. Here’s a look at some of the main technologies involved:
Programming Skills: Strong programming abilities are essential for creating and maintaining cloud services. While there are specialized programming languages, proficiency in languages like Java, Python, and others is often required.
Database Management: Cloud computing frequently involves handling large amounts of data. Knowledge of SQL, NoSQL, and data distribution technologies like Hadoop is important for optimizing performance and ensuring data consistency.
Operating Systems: When working with Infrastructure-as-a-Service (IaaS), familiarity with operating systems, especially Linux, is crucial. Understanding the Linux kernel and command-line interface (CLI) is particularly beneficial.
Software Development: Cloud-based services often take the form of Software-as-a-Service (SaaS). Familiarity with development practices like DevOps, as well as tools like containerization and virtualization, is highly valued.
Web Technologies: Since many cloud services are web-based, understanding web technologies like XML, WSDL, and API design architectures such as SOAP and REST is important.
Networking and Security: Cloud computing relies on robust network connections. Cloud engineers need to be well-versed in network protocols and security measures, including secure access control.
Getting Started in Cloud Computing
One of the most effective ways to enter the cloud computing field is by obtaining a certification from a cloud service provider. These certifications are usually platform-specific and focus on the technologies supported by that platform. Some popular certifications include:
In addition to these cloud-specific certifications, there are other certifications that are closely related to cloud computing:
Upskilling in related fields like data science, IT, and technology management can also be beneficial for a career in cloud computing.
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In the last decade, the integration of AI with the gig economy has become one of the most influential phenomenon that impact the world of work. To underprivileged societies this intersection provides a chance to get a job, develop professional competencies and become economically active. AI is very much a progressive contributor to modern day society that has the potential of demolishing barriers that have existed for decades and make way for fairness in the job market. Nevertheless, there are also just as much threats that need to be met in order to provide the opportunities that this transformation may bring to its citizens inclusive of everyone.
Both, AI and gig work will become an excellent opportunity to change the job market for employees who have been left with no job opportunities. The modern computing and advanced AI techniques can help the platforms to find proper workers for the proper job and connect them according to their skills, abilities and lifestyle preferences. To the less privileged families and individuals, they are sources of basic needs, especially employment for such groups as those residing in the rural areas, disabled persons or those discriminated against due to their color or origin.
In addition, the gig economy avails workers an opportunity to operate in global markets eradicating geographical barriers. By adopting artificial intelligence, gig workers are benefited in identifying their areas of weakness and even skills to improve on and secure higher earnings. Such democratization of work opportunities brings forth the ability to construct careers independently which promote the aspect of economic enfranchisement and upward mobility.
Two of the biggest benefits of AI and gig work are that they offer opportunities for work regardless of some conventional constraints. AI can avoid discriminations in employing people, where the rates of pay and other employee conditions depend on the qualifications and experiences of the applicants rather than their race, gender or socio-economic standards. This has the possibility to create a fairer employment opportunities whereby people especially the disabled are given the opportunities they need rather the situation they are in.
Besides, AI platform can implement training and skill upgrade initiatives where the workers can learn the necessary skills to fit the available job market. For such people and especially for the communities that are disadvantaged in terms of access to basic amenities, education as well as employment opportunities this can be a total game changer.
To achieve the goal of AI and gig work they must consider making platform more inclusive for workers. This entails design of user interfaces that can suit those who are not so much conversant with technology and that the available opportunities do not lock out the less privileged. Also there is a need for good payment and clear policies of the platform so that freelancers and workers can decide when and where to work.
Community support is also imperative Stigma and information disparity are the main challenges of a healthy society. Through building a community of gig economy workers, one is able to ensure that they have a place they belong to and chances to be mentored or to mentor others. This can assist persons to gain confidence, acquire new skills, and be made to understand how to go about in the gig economy if they are from marginalised groups.
However, a few issues have to be considered to make AI and any gigs more inclusive for diverse people and deprived communities. Among the challenges, there is the so-called ‘digital divide’. To be able to take the gig employment opportunities, the stakeholders need internet, devices, and digital literacy skills. Lacking such resources, the possibilities of the AI and gig work can remain so far away from a great number of individuals.
Additionally, freelancers are usually not entitled to the so-called employee’s privileges, including affordable health insurance, pension contributions, and a stable income. The costs could be somewhat discouraging to implement especial for people in the underprivileged areas of society who are struggling to make ends meet. It is therefore the responsibility of the policymakers and the operators of these platforms to put in place mechanisms that will ensure that the welfare of these gig workers is guarded at all times.
Last but
BMC is enhancing mainframe management by introducing generative artificial intelligence (AI) assistants. One of their latest tools, available in beta, helps explain code functionality.
John McKenny, the senior vice president and general manager for Intelligent Z Optimization and Transformation at BMC, announced the launch of BMC Automated Mainframe Intelligence (AMI) DevX Code Insights. This tool, accessible via a chat interface, assists in debugging code written in various languages, understanding system processes, and making more informed decisions.
BMC is training large language models (LLMs) for this purpose. The AMI DevX Code Insights is just one of several AI agents BMC plans to offer through a unified console. These LLMs might be developed by BMC or based on third-party platforms, and organizations can even use their custom-built LLMs.
BMC is also inviting organizations to join a Design Program, granting access to new generative AI features as they develop. These AI agents will act like subject matter experts (SMEs) for specific tasks, offering more than just prompt-based question-answering. They will provide insights and guidance to streamline workflows.
Generative AI is a key part of BMC’s long-term strategy to simplify mainframe management over the next three decades. For example, developers will soon be able to use a service catalog to meet their requirements independently, reducing their reliance on IT operations teams.
The ultimate aim is to make mainframes as easy to manage as any distributed computing platform, requiring fewer specialized skills. While BMC is not alone in this endeavor, the rise of generative AI will significantly speed up the process.
This advancement is particularly important as more AI models are deployed on mainframe platforms, which already house vast amounts of data. It's generally more efficient to bring AI to existing data rather than moving data to new platforms.
IT teams may also need to reconsider which workloads run on which platforms. Although not all organizations use mainframes, those that do can lower overall IT costs by consolidating more workloads on their mainframes, thanks to specialized mainframe licenses.
In summary, as AI simplifies workload management regardless of location, IT teams will likely become more uniform over time.
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