Generative AI Engineer

Role: Manager \AD - Generative AI

Location: Bangalore

Key responsibilities include:

AI Solution Development:

• Design, develop, and deploy Generative AI models and solutions that address complex business challenges across advisory, tax, and audit services.
• Leverage platforms such as Databricks for data engineering and AI model development, AI Fabric for orchestration and deployment, and Snowflake for scalable data management.
• Utilize Azure cloud services to implement and scale AI solutions, ensuring high availability, performance, and security.

Technical Leadership and Collaboration:

• Collaborate with data scientists, AI architects, and software engineers to define technical requirements and develop end-to-end AI solutions.
• Lead the development of AI models from experimentation and prototyping through to production, ensuring alignment with business objectives.
• Work closely with cross-functional teams to integrate AI solutions into existing workflows and systems, optimizing for efficiency and usability.

Coding and Implementation:

• Write high-quality, maintainable code using Python, Scala, or similar programming languages, focusing on AI/ML libraries and frameworks.
• Develop and optimize data pipelines using Databricks, ensuring seamless data flow from ingestion to AI model training and inference.
• Implement AI solutions using AI Fabric, focusing on model orchestration, deployment, and monitoring within a cloud environmen

Data Management and Integration:

• Design and manage data architectures using Snowflake, ensuring data is organized, accessible, and secure for AI model training and deployment.
• Integrate data from various sources, transforming and preparing it for AI model development, ensuring data quality and integrity.
• Work with large datasets, applying best practices for data engineering, ETL processes, and real-time data processing.

Cloud & Infrastructure Management:

1. Deploy AI models and services in Azure, utilizing cloud-native tools and best practices to ensure scalability, reliability, and security.
2. Implement CI/CD pipelines to automate the deployment and management of AI models, ensuring rapid iteration and continuous delivery.
3. Optimize infrastructure for AI workloads, balancing performance, cost, and resource utilization.

Performance Tuning and Optimization:

1. Continuously monitor and optimize AI models and data pipelines to improve performance, accuracy, and scalability.
2. Implement strategies for model fine-tuning, hyperparameter optimization, and feature engineering to enhance AI solution effectiveness.
3. Troubleshoot and resolve technical issues related to AI model deployment, data processing, and cloud infrastructure.

Innovation and Continuous Improvement:

1. Stay updated with the latest advancements in Gen AI, cloud computing, and big data technologies, applying new techniques to improve solutions.
2. Experiment with emerging technologies and frameworks to drive innovation.
3. Contribute to the development of AI best practices, coding standards, and technical documentation to ensure consistency and quality across projects.

About KPMG Delivery Network (KDN)

KPMG Global Services (KGS) India is a strategic global delivery organization that works with over 50 KPMG firms to provide a progressive, scalable and customized approach to business requirements. Established in 2008, KGS India has been consistently growing, currently employing around 22,000 individuals across eight locations in India — Bengaluru, Gurugram, Hyderabad, Mumbai, Kochi, Noida, Kolkata, and Pune.

KGS provides a range of Advisory, Tax, and Audit support services to KPMG firms around the world, and we have received recognition for our inclusive practices and policies in the industry.

Come as you are at KGS

As a firm, we are deeply committed to diversity, inclusion, and equity at our workplace. We offer a safe and inclusive environment built on trust, where all our colleagues can bring their authentic selves to work and know that their uniqueness is valued. We prohibit unfair treatment of applicants and employees and discrimination on any ground, including but not limited to, caste, religion, color, ancestry, marital status, medical condition, sex, gender identity and/or expression, sexual orientation, age, nationality, cultural origin, family or parental status, defense veterans, physical, mental or sensory disability, or any other status or characteristic protected by applicable Indian laws and regulations.

This role is for you if you have the below:

Educational Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Advanced certifications in AI/ML, cloud computing, or data engineering are advantageous.

Work Experience:

• 8 to 14 years of experience in AI, Machine Learning, or related fields, with hands-on experience in developing and deploying AI solutions.
• Proven experience with AI frameworks such as TensorFlow, PyTorch, and experience in working with Databricks, AI Fabric, and Snowflake.
• Extensive experience with Azure cloud services, including AI and data services, and a strong background in cloud-native development.
• Expertise in coding with Python, Scala, or similar languages, with a focus on AI/ML libraries and big data processing.

Skills:

• Proficiency in designing and coding AI models, data pipelines, and cloud-based solutions.
• Strong understanding of AI/ML algorithms, data engineering, and model deployment strategies.
• Experience with cloud infrastructure management, particularly in Azure, and the ability to optimize AI workloads for performance and cost.
• Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team environment.
• Strong communication skills, with the ability to articulate complex technical concepts to technical and non-technical stakeholders.