Welspun GCC - RPA Automation Engineer - Automation Anywhere (4-9 yrs)

Job Description :

- Lead the design and development of Al models and RPA solutions to automate business processes.

- Collaborate with various teams to understand business processes and identify areas for automation.

- Manage the integration of Al/RPA solutions into existing systems and ensure their optimal performance.

- Conduct system integration testing to ensure the functionality and efficiency of Al/RPA solutions.

- Utilize tools such as Automation Anywhere, Blue Prism, Tensorflow, Pytorch, and cloud platforms (AWS,GCP, Azure) in the development and implementation of Al/RPA solutions,

- Optimize processes through the application of Al/RPA solutions and monitor their effectiveness,

- Stay updated with the latest Al/RPA technologies and trends and implement them as appropriate.

- Ensure accountability and customer focus in all Al/RPA projects.

- Communicate effectively with all stakeholders, including team members, management, and customers.

- Manage changes effectively to ensure minimal disruption to business processes.

- Develop and orchestrate Al models in real-world applications, ensuring their effectiveness and efficiency.

Functional Competencies :

- RPA Development : The candidate should have a strong understanding of Robotic Process Automation (RPA) concepts and the ability to design, develop, and implement RPA solutions to automate repetitive tasks and manual processes.

- Al/ML : proficiency in Artificial Intelligence and Machine Learning is required.

The candidate should be able to design and implement Al/ML models to solve complex business problems.

- System Integration Testing : The candidate should have experience in conducting system integration testing to ensure that all components of the system work together seamlessly.

- Automation Anywhere, Blue Prism : Expertise in RPA tools like Automation Anywhere and Blue Prism is essential.

The candidate should be able to develop bots and automate processes using these tools.

- Process Optimization : The candidate should have the ability to analyze current processes, identify areas for improvement, and implement solutions to optimize these processes.

- NLP, Tensorflow, Pytorch : Proficiency in Natural Language Processing and deep learning frameworks like Tensorflow and PYtorch is required.

The candidate should be able to develop and implement NLP models and deep learning algorithms.

- AWS, GCP, Azure : The candidate should have experience working with cloud platforms like AWS, GCP, and Azure. They should be able to deploy and manage applications on these platforms.