Embark on a dynamic career at EY, a global leader dedicated to building a better working world. Join a supportive and inclusive culture where your unique contributions are valued. As part of Global Delivery Services, you will contribute to EY’s growth agenda by providing expert support across various service lines, leveraging innovation and technology.

This role focuses on designing, building, and deploying production-grade AI systems. You will operate as a key individual contributor with the opportunity to lead initiatives, translating complex business needs into scalable and robust technical solutions. Your expertise in Generative AI, Agentic AI, and core Machine Learning principles will be instrumental in driving impactful AI advancements.

Take ownership of AI features from concept to deployment, including problem framing, model development, and API integration.

Design, develop, and implement production-ready AI systems that scale effectively on cloud platforms.

Collaborate closely with stakeholders to understand and translate business requirements into practical technical solutions.

Develop and integrate RESTful APIs for AI models, ensuring seamless incorporation into existing services.

Optimize application performance and scalability to handle high-volume data and user loads.

Manage the deployment and operational aspects of AI models and services, including CI/CD pipelines, containerization, and robust monitoring.

Provide technical leadership and guidance to junior engineers, fostering a collaborative and growth-oriented team environment.

A Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related discipline is required.

Possess 4-8 years of hands-on software and AI engineering experience, with a strong emphasis on Generative AI.

Demonstrate a proven ability to deliver production-quality AI/ML solutions that meet business objectives.

Exhibit deep proficiency in Python and its associated AI/ML libraries and frameworks.

Showcase substantial experience with Generative AI technologies, including LLMs, prompt engineering, RAG, embeddings, and fine-tuning.

Maintain a solid understanding of Machine Learning and Deep Learning concepts and their practical application.

Possess good working knowledge of Natural Language Processing (NLP) and Transformer-based model architectures.

Have production-level experience in designing and developing REST APIs and integrating AI models into operational services.

Demonstrate a track record of scaling applications and optimizing performance for demanding, high-volume workloads.

Gain hands-on experience with Microsoft Azure cloud services for AI development and deployment.

Acquire experience in deploying and managing models and services in production, utilizing CI/CD, containerization, and monitoring tools.