Join EY GDS Consulting's Gen AI team as a Senior AI Developer and be at the forefront of innovation. This role offers a unique opportunity to shape the future of AI within a global organization. You will leverage your passion for data, analytics, and technology to develop and implement cutting-edge AI capabilities.

EY is dedicated to fostering a career path as unique as you are, providing the global scale, support, and inclusive culture needed to thrive. Your perspective is invaluable in helping EY achieve even greater success and build a better working world.

Design and deploy sophisticated AI and Gen AI applications across major cloud environments like Azure, AWS, and GCP. Collaborate closely with data engineers to build and refine AI/ML models. Translate complex business requirements into scalable, operable solutions by partnering with clients and stakeholders.

Take a lead role in architectural decisions, contributing to the development of industry-wide use cases and robust architectures for AI/ML and Generative AI. Define engineering best practices and identify key opportunities for generative AI to deliver significant business value. Create Proofs of Concept (POCs) and Proofs of Value (POVs) for diverse use cases.

Produce high-quality, efficient, and testable code, primarily in Python. Stay abreast of the latest AI advancements and evaluate state-of-the-art technologies to drive innovation. Mentor junior AI engineers on coding best practices and problem-solving techniques, and facilitate design and architecture workshops.

A minimum of 5-8 years of professional experience in building and deploying AI and Generative AI solutions, whether on-premises or on cloud platforms, is essential. A strong foundation in data processing, data structures, algorithms, and machine learning is required.

Key technical proficiencies include hands-on experience with deploying AI/ML solutions on cloud platforms such as Azure, AWS, or Google Cloud. Experience in orchestrating Large Language Models (LLMs) on cloud platforms like Azure OpenAI, AWS Bedrock, or GCP Vertex AI is highly desirable.

Familiarity with agentic frameworks (e.g., Semantic Kernel, CrewAI, LangGraph) is beneficial. You should possess strong programming skills, particularly in Python and potentially PySpark, alongside experience in SQL and data modeling. Experience with microservice-based architecture and AI solution implementation is a plus.

Excellent problem-solving abilities, the capacity to link AI capabilities to tangible business value, and strong communication and presentation skills are crucial. Proven experience in deploying AI/ML solutions on platforms like Kubernetes, Web Apps, or Databricks is expected. Familiarity with MLOps concepts, code versioning, MLFlow, and batch/real-time endpoints is advantageous.