Join EY and contribute to building a better working world. As a Cloud Engineering Senior Engineer focused on API, Full Stack, and AI/ML, you will leverage your extensive experience to design, develop, and modernize cloud-native applications and enterprise API ecosystems. This role is pivotal in driving digital transformation and innovation for our enterprise clients, enhancing scalability and operational efficiency.

We are seeking a dynamic professional with a strong blend of technical expertise and client-facing advisory skills. You will lead application modernization initiatives, spearhead API transformations, and champion AI/ML adoption through impactful proof-of-concepts within complex enterprise environments.

Design, develop, and optimize cloud-native applications and enterprise APIs across Azure, AWS, and GCP. Build secure, scalable, and high-performing applications using modern Full Stack technologies and Python frameworks. Implement RESTful APIs, GraphQL services, microservices, and enterprise integration solutions, with a strong focus on API lifecycle management and security.

Apply AI/ML and Generative AI technologies to create intelligent business applications and automation solutions, including those leveraging Large Language Models (LLMs), RAG architectures, and AI Agents. Develop automation frameworks and engineering accelerators using Python and Terraform. Support cloud modernization efforts involving containers, Kubernetes, DevSecOps, CI/CD, and Infrastructure as Code. Execute Proof of Concepts (PoCs) and pilot implementations, developing comprehensive technical documentation and architecture diagrams for client engagements.

A minimum of 6 years of experience in Cloud Engineering, Enterprise Application Development, API Engineering, and Full Stack Development is required. You should possess a solid understanding of cloud-native architecture principles, including microservices, distributed systems, containers, and event-driven architectures. Proven experience in designing and developing enterprise APIs and cloud-native applications is essential.

Demonstrated hands-on experience with AI/ML, Generative AI, and modern application development technologies is crucial. Familiarity with cloud platforms such as Azure, AWS, and GCP is expected, alongside a strong understanding of DevSecOps, Infrastructure as Code, CI/CD, and engineering automation practices. Prior experience in client-facing advisory, consulting, or enterprise engineering roles, coupled with strong analytical, problem-solving, and communication skills, is necessary. A Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related discipline is required.