Artificial Intelligence Engineer

Job Title: EY - GDS Consulting - AIA - Gen AI - Senior

Title: Senior AI Developer (GenAI)

Educational qualification: BTech/Masters/PhD

Your key responsibilities

• Design and implement AI/Gen AI applications, systems, and infrastructure across major clouds (Azure, AWS and GCP)
• Collaborate with data engineers & build AI/ML models.
• Collaborate with clients & stakeholders to translate business and functional requirements into robust, scalable, operable solutions.
• Participate in architectural decisions, contribute to the development of architectures for industry-wide use cases, and design architectures for AI/ML and Generative AI
• Set the standards for engineering best practices.
• Identify opportunities where generative AI can provide value and solve business problems.
• Responsible for creating POCs and POVs across horizontals and industry use cases.
• Write high-quality, efficient, testable code in Python and other languages.
• Stay up to date with the latest AI trends and evaluate state-of-the-art AI technologies/framework to drive innovation.
• Facilitate design and architecture workshops and mentor AI engineers in coding best practices and problem-solving.

Skills and Attributes

Professional Experience

• A minimum of 5-8 years in building and deploying AI and Gen AI solutions on-premises or on cloud platforms.

Preferred / GoodtoHave Skills

• Hand-on experience in deploying AI/ML solutions on different cloud platforms like Azure, AWS and/or Google Cloud.
• Experience in using and orchestration LLM models on cloud platforms i.e., OpenAI @ Azure/AWS Bedrock/ GCP Vertex AI or Gemini AI
• Experience in Agentic frameworks building and deploying (e.g. Semantic Kernel, CrewAI, LangGraph etc.)
• Experience in writing SQL and data modelling.
• Experience in designing and implementation of AI solution using microservice based architecture.
• Understanding of machine learning, deep learning, NLP and GenAI.
• Strong programming skills in Python and/or pyspark.
• Proven experience in integrating authentication security measures within machine learning operations and applications.
• Excellent problem-solving skills and ability to connect AI capabilities to business value.
• Strong communication and presentation skills.
• Proven experience in AI/ML solution deployment process on Kubernetes, Web Apps, Databricks or on similar platforms.
• Familiarity with MLOps concepts and tech stack. Good to know code versioning, MLFlow, batch prediction and real-time end point workflows.
• Familiarity with Azure DevOps / GitHub actions/ Jenkins / Terraform / AWS CFT etc.
• Familiarity with Responsible AI concepts
• strong Background in Azure Based AI and Data technologies is a must.
• Knowledge of other Hyperscalars will be additional Advantage

Other Responsibilities:

• Manage end to end project delivery- scoping, solutioning, designing, developing, testing, deploying or maintaining.
• Ensuring the solutions meet the client requirements and expectations.
• Communicate effectively with the clients and internal stakeholders throughout the project.
• Identify new opportunities and generate proposals for potential clients.
• Present the solutions and showcase the value proposition to senior stakeholders.