Digital Next : IA : Senior - Gen AI

Aimlroles; Mumbai; Presencial; INR 3.000.000 - 5.500.000; Jornada completa

Descripción de la vacante

KPMG India is seeking a highly skilled Generative AI Engineer to join our delivery team. The role focuses on designing, building, and deploying enterprise-grade AI solutions on Databricks, Microsoft Fabric, Azure, and Snowflake.

You will combine hands-on engineering with AI/ML frameworks and scalable cloud architectures to deliver measurable business value. Education and experience requirements include CS/Engineering/Data Science degrees and 3+ years in Generative AI.

Formación

• 3+ years of hands-on Generative AI or data engineering experience.
• Experience building AI/ML solutions with TensorFlow, PyTorch, or equivalent.
• Hands-on cloud experience (AWS/Azure/GCP).

Responsabilidades

• Architect, design, and deliver Generative AI and machine learning solutions across service lines.
• Develop end-to-end AI solutions with data engineering and model development practices.
• Utilize leading cloud services to build secure, scalable AI solutions.
• Write clean, efficient code in Python/JavaScript for AI/ML and data processing.
• Build scalable data pipelines for ingestion, feature engineering, model training and inference.
• Implement model lifecycle management, deployment automation, and monitoring.
• Design and maintain CI/CD pipelines to enable automated model deployment and continuous improvement.
• Continuously optimize cloud infrastructure and AI workloads for performance and cost efficiency.
• Stay up to date with Generative AI, LLMs, cloud platforms, and big-data ecosystems.
• Contribute to engineering standards, reusable assets, and technical documentation.

Conocimientos

Python

JavaScript

AI/ML basics

MLOps

Data engineering

Distributed processing

Cloud architecture

Communication

Analytical skills

Educación

Bachelors or Masters in CS/Engineering/Data Science

AI/ML, Azure, cloud certs

Herramientas

TensorFlow

PyTorch

Databricks

Azure

Snowflake

Microsoft Fabric

AWS

GCP

Descripción del empleo

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Job Description

KPMG India Services is seeking a highly skilled Generative AI Engineer to join our delivery team. The Generative AI Engineer will play a critical role in designing, building, and deploying enterprise‑grade AI solutions using modern cloud and data platforms such as Databricks, Microsoft Fabric (AI Fabric), Azure, and Snowflake.

This role requires strong hands‑on engineering capability combined with a solid understanding of AI/ML frameworks and scalable cloud architectures to deliver measurable business value.

Education

• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.


• Relevant certifications in AI/ML, Azure, cloud computing, or data engineering are a strong plus.

Experience

• 3+ years of hands‑on experience in Generative AI, Machine Learning, or advanced data engineering roles.


• Demonstrated experience building and deploying AI/ML solutions using frameworks such as TensorFlow, PyTorch, or equivalent.


• Hands‑on experience with cloud platforms such as AWS/Azure/GCP.

Skills

• Strong proficiency in Python, JavaScript, or similar programming languages.


• Solid understanding of AI/ML algorithms, model deployment patterns, and MLOps practices.


• Expertise in data engineering, distributed processing, and cloud‑based architecture.


• Strong analytical and problem‑solving skills with the ability to work effectively in cross‑functional, global teams.


• Excellent communication skills, with the ability to translate complex technical concepts for both technical and non‑technical stakeholders.

Key Responsibilities

1. AI Solution Design & Development

• Architect, design, and deliver Generative AI and machine learning solutions to address complex business challenges across KPMG service lines.


• Develop end‑to‑end AI solutions incorporating robust data engineering and model development practices, leveraging industry‑standard tools for orchestration, deployment, and scalable, governed data management.


• Utilize leading cloud services to build secure, resilient, and highly scalable AI solutions.

2. Technical Leadership & Collaboration

• Work closely with data scientists, AI architects, platform engineers, and business stakeholders to define solution designs and technical requirements.


• Drive AI initiatives from experimentation and proof‑of‑concept through to enterprise‑scale production deployments.


• Collaborate with cross‑functional teams to embed AI capabilities into existing platforms, workflows, and business processes.

3. Engineering & Implementation

• Write clean, efficient, and maintainable code using Python, JavaScript, or similar languages, with a focus on AI/ML and distributed data processing.


• Build and optimise scalable data pipelines to support data ingestion, feature engineering, model training, and inference.


• Implement model lifecycle management, deployment automation, and monitoring using industry‑standard tools and cloud‑native services.

4. Cloud & Platform Operations

• Deploy, manage, and operate AI solutions on Cloud, adhering to cloud‑native best practices for security and reliability.


• Design and maintain CI/CD pipelines to enable automated model deployment and continuous improvement.


• Continuously optimising cloud infrastructure and AI workloads for performance, scalability, and cost efficiency.

5. Performance Optimization & Reliability

• Monitor and tune AI models, data pipelines, and infrastructure to ensure optimal performance and scalability.


• Apply model fine‑tuning, hyperparameter optimisation, and feature engineering techniques to improve solution accuracy and effectiveness.


• Diagnose and resolve production issues related to data processing, model behaviour, and cloud infrastructure.

7. Innovation & Continuous Improvement

• Stay up to date with advancements in Generative AI, large language models (LLMs), cloud platforms, and big‑data ecosystems.


• Explore and evaluate emerging tools, frameworks, and architectures to enhance solution quality and delivery speed.


• Contribute to engineering standards, reusable assets, and technical documentation to support consistency and quality across KPMG India Services.

Equal employment opportunity information

KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.