EY - GDS Consulting - AI and DATA -...
Responsibilities
Qualifications & Requirements
Experience Level: Senior Level
Full Job Description
At EY's Global Delivery Services (GDS) Consulting, within the AI and Data practice, we are seeking a talented AI Engineering Senior to join our team in Bengaluru, India. You will be instrumental in engineering, deploying, and operating AI-powered services and APIs in production environments. This role emphasizes proficiency in Python, API development, robust deployment strategies, and end-to-end MLOps/DevOps practices, particularly on AWS and Azure cloud platforms. You will collaborate closely with data science, machine learning, and platform engineering teams to seamlessly transition AI models and capabilities from development environments (like notebooks) into reliable, secure, and scalable production services.
Key Responsibilities
- Design, build, and maintain production-grade AI services and APIs, taking ownership of their reliability, scalability, and performance according to defined Service Level Objectives (SLOs).
- Implement MLOps best practices, including experiment tracking, model packaging, CI/CD pipelines for machine learning models, automated testing, feature and model registries, and telemetry, to accelerate the time-to-market for AI solutions.
- Drive DevOps automation, utilizing Infrastructure as Code (IaC), containerization, and orchestration technologies. Ensure secure delivery through principles of least privilege, effective secrets management, and policy-as-code implementation.
- Lead the deployment of AI components onto AWS/Azure, leveraging services such as containers, serverless architectures, and managed ML platforms. Ensure comprehensive observability and establish robust rollback plans.
- Collaborate effectively with cross-functional teams to translate product and analytical requirements into well-defined APIs, contracts, and Service Level Agreements (SLAs).
Must-Have Skills
- Experience with MLOps tools and frameworks such as MLflow, Kubeflow, SageMaker, or Azure ML; CI/CD for ML; model registry management; and monitoring solutions.
- Proficiency in DevOps practices, including Docker, Kubernetes, Infrastructure as Code (Terraform/Bicep), and CI/CD tools like GitHub Actions, GitLab Actions, or Azure DevOps.
- Strong Python skills, with experience in writing production-quality code, implementing testing strategies, and managing package dependencies.
- Hands-on experience deploying AI solutions to cloud platforms like AWS (EKS, ECS/Fargate, Lambda, API Gateway) or Azure (AKS, App Service, Functions, Application Gateway).
- Expertise in API development using frameworks like FastAPI or Flask, with knowledge of OpenAPI/Swagger specifications, authentication/authorization mechanisms, rate limiting, and API versioning.
Good-to-Have Skills
- Familiarity with Generative AI (GenAI) concepts, agentic systems, vector databases, and fundamentals of prompt engineering.
Qualifications and Experience
- Bachelor's or Master's degree (B.Tech/M.Tech/MS) in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
- A minimum of 4 years of professional experience in AI Engineering.
EY is committed to building a better working world by creating long-term value for clients, people, and society, and by building trust in capital markets. Enabled by data and technology, our diverse teams in over 150 countries help clients grow, transform, and operate by providing trust through assurance and innovative consulting services. We tackle complex global issues across assurance, consulting, law, strategy, tax, and transactions, driven by our commitment to asking better questions and finding new answers.
Company
EY
EY is a global leader in professional services, dedicated to building a better working world. We help create long-term value for clients, our people, and society by fostering trust and enabling busine...