Surender's Journey to Becoming a Senior Generative AI Manager

Have you ever wondered how an experienced IT professional can successfully transition into Artificial Intelligence? Meet Surender Arumugam from Chennai, who transformed his career from mainframe technologies to becoming a Senior Generative AI Manager at Cognizant through continuous learning and upskilling.

His journey wasn't easy. Balancing a full-time job while learning Python, Machine Learning, and Data Science required dedication and consistent practice. Joining DataMites gave him the practical skills, hands-on project experience, and confidence to make a successful transition into AI.

Today, Surender leads Generative AI initiatives and shares his inspiring career journey, valuable learning experiences, and practical advice for aspiring AI professionals looking to build a successful career in Artificial Intelligence.

How Surender Transitioned into Generative AI with DataMites

Surender's journey from an experienced mainframe professional to a Senior Generative AI Manager highlights the value of continuous upskilling and practical learning. Through DataMites' industry-focused training, hands-on projects, and expert mentorship, he successfully transitioned into Artificial Intelligence and built a rewarding career in Machine Learning, Deep Learning, and Generative AI.

Q1. Can you introduce yourself and tell us about your background?

Thank you for having me. I'm Surender Arumugam from Chennai, and I have over 18 years of experience in the IT industry, primarily with Cognizant. I started my career in mainframe technologies, where I worked for nearly ten years before transitioning into automation. Over the last few years, I've moved into Artificial Intelligence and Generative AI, and currently, I work as a Senior Generative AI Manager at Cognizant.

Q2. What motivated you to move into Artificial Intelligence?

When cloud technologies and automation started growing rapidly, I realized there was a strong demand for intelligent automation. At that time, I honestly didn't know the difference between Artificial Intelligence and Machine Learning, but I knew I had to upskill to stay relevant in the industry. That's when I started exploring AI and looking for the right learning platform.

Q3. Why did you choose DataMites ?

I spent nearly two months researching different institutions. What impressed me most about DataMites was the curriculum. It covered the topics I had been looking for, and the course content was structured in a practical and easy-to-understand manner. That gave me confidence that I would learn the right skills required by the industry.

Q4. Which course did you enroll in, and how was your learning experience?

I enrolled in the Certified Data Scientist course after seeing the growing demand for IT courses, especially in AI and data science. We started with Python and gradually moved into Machine Learning, Artificial Intelligence, and Deep Learning. The instructors explained every topic patiently, answered all our questions, and helped us understand the concepts clearly, making the learning experience both enjoyable and valuable.

Q5. How did regular practice help you during the course?

Practice made all the difference. Our instructor encouraged us to code regularly, complete assignments, and work on weekly exercises. Her continuous feedback helped us improve, and within a few weeks, we had the confidence to code and discuss technical concepts comfortably.

Q6. How valuable were the capstone projects?

The capstone projects helped me apply everything I had learned to real-world business problems. Working as a team, we received continuous guidance and feedback from the faculty, which strengthened my practical skills and gave me valuable industry exposure.

Q7. What was the biggest challenge during your learning journey?

The biggest challenge was balancing my full-time job with my studies. Managing office responsibilities while working on assignments and capstone projects wasn't easy, but my commitment to learning kept me motivated throughout the journey.

Q8. Did you get immediate career opportunities after completing the course?

Not immediately. My first goal was to create opportunities within my own organization. The knowledge and confidence I gained helped me contribute to AI discussions, work on projects, and gradually transition into Machine Learning and Data Science.

Q9. How did the training help you in your workplace?

The biggest difference was confidence. Before learning AI, I would simply listen to discussions. After the training, I could actively contribute to technical conversations, understand project requirements, and become part of AI projects with confidence.

Q10. How did your career progress after entering AI?

I started with Machine Learning and Data Science projects before moving into Deep Learning and eventually Generative AI. Today, I work as a Senior Generative AI Manager, a journey built through continuous learning, hands-on experience, and embracing new opportunities.

Q11. What kind of Generative AI projects do you currently work on?

Due to confidentiality, I can't share specific project details, but my work focuses on building Generative AI solutions that automate content creation. Tasks like preparing reports and documentation can now be completed much faster, helping organizations improve productivity and efficiency.

Q12. Which tools and technologies do you use in Generative AI projects?

The technology stack depends on the client's requirements. We commonly use Azure, AWS, Google Cloud, Azure OpenAI, Python, Databricks, FastAPI, and Azure AI Search. Generative AI projects are highly collaborative, involving backend developers, data engineers, DevOps, and testing teams.

Q13. What advice would you give to freshers who want to build a career in AI?

My first advice is to do your research before joining any AI course. Don't choose Artificial Intelligence just because it's trending. Genuine interest, continuous practice, and consistent effort are what ultimately determine your success.

Q14. What skills do companies actually look for in AI professionals?

From my experience, companies don't just look for candidates who know syntax. They value professionals who understand concepts deeply and can explain them confidently. That comes from hands-on practice, real-world projects, and applying what you've learned.

Q15. How should candidates prepare for AI interviews?

First, understand the job description clearly. AI, Machine Learning, Deep Learning, and Generative AI require different skill sets. Prepare specifically for the role you're applying for and demonstrate practical knowledge related to that specialization during interviews.

Q16. Is Artificial Intelligence replacing traditional jobs?

I don't believe AI is replacing jobs. It's becoming an integral part of every industry by improving efficiency and automating repetitive tasks. Instead of worrying about AI, focus on learning it and becoming the person who drives it.

Q17. What final advice would you like to give aspiring AI professionals?

My advice is simple: start learning now. Technology is evolving rapidly, so continuous upskilling is essential to stay relevant. Embrace AI, keep learning, build projects, and become part of the technological transformation.

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• What Are Graph Neural Networks? Simple Guide for Beginners
• What is Artificial Narrow Intelligence?

Surender's Key Takeaways on Building a Career in Artificial Intelligence

Surender's journey shows how continuous learning, practical experience, and dedication can help professionals successfully transition into Artificial Intelligence.

• Background: Surender is from Chennai with over 18 years of IT experience.
• Career Transition: He moved from mainframe technologies to automation and later into AI and Generative AI.
• Upskilling Journey: He chose to learn AI to stay relevant with changing industry demands.
• Training Choice: He enrolled in the Certified Data Scientist program at DataMites to gain structured AI knowledge.
• Learning Experience: The program helped him build skills in Python, Machine Learning, Data Science, and Deep Learning.
• Practical Exposure: Hands-on projects and capstone assignments helped him apply AI concepts to real-world problems.
• Career Growth: He gradually transitioned from Machine Learning projects to Deep Learning and Generative AI.
• Current Role: He currently works as a Senior Generative AI Manager.
• Technical Skills: He works with technologies such as Python, cloud platforms, Azure OpenAI, Databricks, and AI tools.
• AI Career Advice: He recommends focusing on practical skills, continuous learning, and strong conceptual understanding.
• Future Perspective: He believes professionals should embrace AI and adapt to evolving technologies.

Refer to these articles:

• How Manoj Started His Python AI Developer Career as a Fresher
• How Safeer Landed His First AI Engineer Job as a Fresher
• How Kanchi Built Her Career in Artificial Intelligence and Automation

Surender’s journey shows how continuous learning and practical experience can help professionals transition into Artificial Intelligence. He chose the Artificial Intelligence Course in Chennai at DataMites to upskill in AI and build industry-relevant skills. Through structured training, hands-on projects, and expert guidance, he developed knowledge in Python, Machine Learning, and Deep Learning, helping him successfully move into AI projects and become a Senior Generative AI Manager.

DataMites Institute offers a 9-month Artificial Intelligence program focused on practical learning through hands-on training, real-world projects, and modern AI tools. With specialized tracks like AI Engineer, AI Specialist, AI for Product Managers, AI Foundation, and Certified NLP Professional, along with IABAC and NASSCOM FutureSkills certifications, the program helps learners build industry-ready skills and confidence for AI careers.

As Artificial Intelligence continues to reshape industries and create new career opportunities, gaining practical expertise has become essential for aspiring professionals. DataMites Institute provides classroom-based Artificial Intelligence Courses in Hyderabad, Ahmedabad, Coimbatore, Bangalore, Pune, Mumbai, and Delhi, combining expert-led sessions, practical assignments, hands-on projects, and industry-focused learning approaches to help learners build the skills needed for AI-driven career paths.