DE-Cloud AI Engineer-F02

📍 Job Overview

• Job Title: DE-Cloud AI Engineer-F02
• Company: EY
• Location: Pune, Mahārāshtra, India
• Job Type: On-site
• Category: AI Engineer
• Date Posted: 2025-06-18

🚀 Role Summary

• Develop, deploy, and optimize AI models and solutions, ensuring they meet performance, scalability, and security requirements.
• Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.
• Provide technical support and troubleshooting for AI-related issues.
• Stay updated on the latest advancements in AI/ML technologies and experiment with new AI tools and frameworks to enhance existing solutions.
• Contribute to the adoption of best practices for AI model lifecycle management.

💻 Primary Responsibilities

• AI/ML Model Development:

  • Develop and train machine learning models using frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, and Scikit-learn.
  • Leverage large language models (LLMs) and work on cloud LLM deployments.
  • Build AI agents and have a solid understanding of agentic frameworks.
  • Implement and fine-tune AI models for various business applications.

• AI/ML Deployment and Optimization:

  • Deploy machine learning models on cloud platforms (e.g., AWS, Azure, GCP).
  • Optimize AI pipelines for both real-time and batch processing.
  • Understand concepts around model fine-tuning, distillation, and optimization.
  • Monitor and maintain the performance of deployed models, ensuring they meet business requirements.

• Cloud Integration:

  • Integrate AI/ML models with existing cloud infrastructure.
  • Utilize cloud services (e.g., AWS SageMaker, Azure AI, GCP AI Hub) to manage AI workloads.
  • Ensure compliance with data privacy and security standards.

• Collaboration and Support:

  • Work closely with the AI Architect to design scalable AI solutions.
  • Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.
  • Provide technical support and troubleshooting for AI-related issues.

• Continuous Learning and Innovation:

  • Stay updated on the latest advancements in AI/ML technologies.
  • Experiment with new AI tools and frameworks to enhance existing solutions.
  • Contribute to the adoption of best practices for AI model lifecycle management.

🎓 Skills & Qualifications

Education:

• Bachelor's or master's degree in computer science, Engineering, or a related field.

Experience:

• At least 5+ years in AI-related roles

Required Skills:

• Proficiency in AI/ML frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud platforms: AWS, Azure, GCP.
• Understanding of data engineering, ETL pipelines, and big data tools (e.g., Apache Spark, Hadoop).
• Hands-on experience with containerization and orchestration tools (Docker, Kubernetes).
• Knowledge of DevOps practices for AI/ML (MLOps).
• Strong understanding of deep learning models, including DNN, LSTM, Transformers, RL, and GNN.
• Experience with Generative AI technologies, including LLMs, model fine-tuning, distillation, and optimization.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.
• Ability to work in a fast-paced, collaborative environment.

Preferred Qualifications:

• Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure AI Engineer) are a plus.
• Proven experience in developing and deploying AI solutions with Python, JavaScript.
• Strong background in machine learning, deep learning, and data modelling.
• Experience in integrating AI models with cloud infrastructure.
• Familiarity with Agile development practices and methodologies.

📊 Compensation & Benefits

Salary Range: Not specified. (Research region-specific AI engineer salaries to provide an estimated range.)

Benefits:

• Continuous learning: Develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: Provide tools and flexibility to make a meaningful impact, your way.
• Transformative leadership: Give insights, coaching, and confidence to be the leader the world needs.
• Diverse and inclusive culture: Embrace who you are and empower you to use your voice to help others find theirs.

Working Hours: 40 hours per week

🎯 Team & Company Context

🏢 Company Culture

Industry: Professional services, focusing on financial services marketplace.

Company Size: Large, global organization with a separate business dedicated exclusively to the financial services marketplace.

Founded: 1903

Team Structure:

• Multi-disciplinary teams from around the world.
• Aligned to key industry groups including Asset management, Banking and Capital Markets, Insurance and Private Equity, Health, Government, Power and Utilities.
• Provides integrated advisory, assurance, tax, and transaction services.

Development Methodology:

• Agile development practices and methodologies.
• Collaborative approach with cross-functional teams, including designers, marketers, and business teams.

Company Website: EY Global Website

📝 Enhancement Note: EY's focus on the financial services marketplace and global team structure offers AI engineers the opportunity to work on diverse projects and collaborate with various industry groups.

📈 Career & Growth Analysis

AI Engineer Career Level: Senior AI Engineer with a focus on model development, deployment, and optimization, as well as cloud integration and collaboration.

Reporting Structure: Reports directly to the AI Architect and works closely with cross-functional teams.

Technical Impact: Designs, develops, and optimizes AI models and solutions, ensuring they meet performance, scalability, and security requirements. Collaborates with teams to integrate AI/ML models with existing cloud infrastructure.

Growth Opportunities:

• Technical specialization in AI/ML, cloud technologies, and data engineering.
• Leadership roles in AI/ML team management and architecture decision-making.
• Career progression to AI Architect or other senior AI/ML roles within the organization.

📝 Enhancement Note: EY's global presence and diverse industry groups provide AI engineers with ample opportunities for career growth and technical specialization.

🌐 Work Environment

Office Type: On-site, with global office locations.

Office Location(s): Pune, Mahārāshtra, India (primary location for this role)

Workspace Context:

• Collaborative workspace with multi-disciplinary teams.
• Access to development tools, multiple monitors, and testing devices.
• Cross-functional collaboration with designers, marketers, and business stakeholders.

Work Schedule: Standard office hours with flexibility for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: EY's global team structure and collaborative workspace offer AI engineers a dynamic and diverse work environment.

🛠 Technology Stack & Web Infrastructure

AI/ML Frameworks:

• Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn

Cloud Platforms:

• AWS, Azure, GCP

Data Engineering & Big Data Tools:

• Apache Spark, Hadoop, ETL pipelines

Containerization & Orchestration Tools:

• Docker, Kubernetes

DevOps Practices for AI/ML (MLOps):

• CI/CD pipelines, automated deployment, model monitoring, and version control

📝 Enhancement Note: EY's use of popular AI/ML frameworks, cloud platforms, and data engineering tools enables AI engineers to work with established and widely-adopted technologies.

👥 Team Culture & Values

AI/ML Team Values:

• Continuous learning and innovation.
• Collaboration and cross-functional teamwork.
• Technical excellence and quality.
• User-centric design and problem-solving.
• Data-driven decision-making and optimization.

Collaboration Style:

• Cross-functional integration between developers, designers, and stakeholders.
• Code review culture and peer programming practices.
• Knowledge sharing, technical mentoring, and continuous learning.

📝 Enhancement Note: EY's focus on collaboration, continuous learning, and technical excellence fosters a supportive and innovative team culture for AI engineers.

⚡ Challenges & Growth Opportunities

Technical Challenges:

• Developing and deploying AI models that meet performance, scalability, and security requirements.
• Integrating AI/ML models with existing cloud infrastructure and ensuring compliance with data privacy and security standards.
• Staying updated on the latest advancements in AI/ML technologies and experimenting with new tools and frameworks.

Learning & Development Opportunities:

• Technical specialization in AI/ML, cloud technologies, and data engineering.
• Leadership roles in AI/ML team management and architecture decision-making.
• Career progression to AI Architect or other senior AI/ML roles within the organization.

📝 Enhancement Note: EY's global presence and diverse industry groups provide AI engineers with ample opportunities for career growth, technical specialization, and leadership development.

💡 Interview Preparation

Technical Questions:

• AI/ML model development and optimization techniques.
• Cloud platform integration and deployment strategies.
• Data engineering and big data tool proficiency.
• Problem-solving and analytical skills assessment.

Company & Culture Questions:

• Understanding of EY's global team structure and industry focus.
• Experience with Agile development practices and methodologies.
• Adaptability to diverse work environments and cross-functional teams.

Portfolio Presentation Strategy:

• Highlight AI/ML model development, deployment, and optimization projects.
• Demonstrate cloud integration and data engineering skills.
• Showcase problem-solving and analytical skills through real-world examples.

📝 Enhancement Note: EY's global presence and diverse industry groups require AI engineers to demonstrate strong technical skills, adaptability, and cultural fit for various roles and teams.

📌 Application Steps

To apply for this AI Engineer position at EY:

1. Submit your application through the application link provided.
2. Customize your resume to highlight relevant AI/ML, cloud, and data engineering skills and experiences.
3. Prepare a portfolio showcasing your AI/ML model development, deployment, and optimization projects, as well as cloud integration and data engineering skills.
4. Research EY's global team structure, industry focus, and Agile development practices to demonstrate your understanding of the organization and its culture.
5. Prepare for technical interviews by brushing up on your AI/ML, cloud, and data engineering skills, as well as problem-solving and analytical skills assessment.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.