KDN India_AI_Full Stack Engineer

About KPMG Delivery Network

The world of global advisory, audit and tax compliance services for large multi-nationals is rapidly changing and heavily dependent on technology. The KPMG Delivery Network (KDN) is a KPMG special purpose member firm offering a way for clients to leverage KPMG top talent and technology platforms through regional teams of specialists, enabling economies of scale and a new way of working that expands beyond local capability together with KDN, KPMG member firms can drive the sales and delivery of global solutions at a competitive price and in a repeatable and consistent manner. As a member of KDN, you'll be a part of the KPMG family working alongside some of our profession's most skilled practitioners on rewarding programs and initiatives that are changing the way business operates, delivering value to our clients, and driving positive change in the communities we serve. You'll be enabling KDN accelerate new ways of working, using cuttingedge technology and working together with our member firms located in nearly 150 countries to help us achieve our ambition to be the most trusted and trustworthy professional services firm. And through your work, you'll build a global network and unlock opportunities that you may not have thought possible with access to great support, vast resources, and an inclusive, supportive environment to help you reach your full potential.

Job Summary :

KPMG Delivery Network (KDN) is seeking an experienced Full Stack Engineer. This role is pivotal in designing, developing, and deploying full-stack solutions that leverage AI technologies, including Generative AI, Machine Learning (ML), and Natural Language Processing (NLP). As a Full Stack Engineer, you will work on building end-to-end AI-powered applications and platforms, integrating frontend and backend technologies, and ensuring seamless user experiences. This role requires a strong background in both frontend and backend development, with a focus on AI use cases.

Job Level: Manager

Experience: 10–12 years

Notice Period: Immediate joiners preferred (30–45 days)

Responsibilities:

1.Full Stack Development:

• Design, develop, and maintain scalable web applications and platforms that incorporate AI models and services.
• Work on both frontend and backend components, ensuring that AI models are effectively integrated into the application stack.
• Build and optimize user interfaces using modern frontend frameworks such as React.js, Angular, or Vue.js.
• Develop robust backend systems using Node.js, Python, or similar technologies, with a focus on API development and data management.

2.AI Integration:

• Collaborate with data scientists and AI engineers to integrate AI/ML models into web applications, ensuring smooth deployment and operation.
• Implement AI-driven features, such as personalized recommendations, predictive analytics, and NLP-based search functionalities, within the application.
• Utilize cloud-based AI services (e.g., Azure AI, AWS SageMaker) to deploy and manage AI models within the application infrastructure.

3.End to End Solution Building:

• Lead the development of AI use cases, from concept through to deployment, ensuring that the full-stack solutions are aligned with business objectives.
• Develop and maintain microservices and APIs that facilitate the integration of AI models with frontend applications.
• Implement data processing and transformation pipelines to support AI model training and inference within the application

4.Collaboration and Cross Function work:

• Work closely with AI teams, including data scientists, AI engineers, and UX designers, to translate AI concepts into functional applications.
• Engage with stakeholders across KPMG member firms to understand their requirements and deliver tailored AI solutions.
• Participate in code reviews, provide technical guidance, and mentor junior developers within the team.

5.Performance Optimization:

• Optimize the performance of AI-driven web applications, ensuring fast load times, scalability, and efficient resource usage.
• Implement security best practices to protect data, including encryption, secure authentication, and compliance with data protection regulations.
• Continuously monitor and improve application performance, implementing updates and patches as needed.

6.DevOps and Continuous Integration:

• Implement CI/CD pipelines to automate the testing, deployment, and scaling of AI-powered web applications.
• Use containerization (Docker, Kubernetes) to manage and deploy AI applications across multiple environments.
• Ensure that the deployment processes are streamlined and that the AI applications can scale to meet demand.

7.Innovation and Continuous Improvement:

• Stay updated with latest advancements in AI, web development, and cloud computing, applying new techniques to improve application functionality.
• Experiment with new technologies and frameworks to enhance the capabilities and performance of AI-driven applications.
• Contribute to the development of best practices and technical standards within KDN.

Skills :

• 8+ years of experience in full-stack development, with a strong focus on AI.
• Proven experience in developing and deploying web applications that integrate AI models and services.
• Hands-on experience with frontend frameworks (React.js, Angular, Vue.js) and backend technologies (Node.js, Python).
• Proficiency in both frontend and backend development, with a strong understanding of web architecture and design principles.
• Strong knowledge of AI/ML frameworks and libraries, and experience integrating AI models into full-stack applications.
• Expertise in cloud platforms (e.g., Azure, AWS) and experience deploying AI models using cloud services.
• Familiarity with DevOps practices, including CI/CD pipelines, containerization, and automated deployment processes.
• Excellent problem-solving skills and the ability to work independently and as part of a cross-functional team.
• Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

Educational Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Certifications in AI/ML, web development, or cloud computing are advantageous.