Artificial Intelligence Engineer

AIA Agentic AI/Gen AI The opportunity EY GDS is seeking a motivated, quality-focused, and hands-on Agentic AI & Generative AI Senior to join our AI team. The ideal candidate will have experience in the Banking domain and strong development exposure in building AI, GenAI, and Agentic AI solutions. As an Agentic AI & Gen AI Senior, you will contribute to the design, development, testing, deployment, and maintenance of AI-powered applications across banking processes. The role requires hands-on experience with Azure AI ecosystem, LLM-based applications, RAG solutions, AI agents, agent orchestration frameworks, and modern software engineering practices . The candidate should be comfortable working with architects, managers, data scientists, and engineering teams to deliver scalable, secure, and production-ready AI solutions. Your key responsibilities Develop and implement Agentic AI, Generative AI, and AI solutions specifically for Banking use cases under the guidance of managers and solution architects. Translate functional and technical requirements into working AI components, APIs, prompts, workflows, agents, and reusable development modules. Build and enhance LLM-powered applications, AI copilots, RAG pipelines, Agentic RAG workflows, autonomous agents, and multi-agent orchestration flows. Work with data scientists, AI engineers, architects, product teams, and banking domain stakeholders to develop high-impact AI solutions. Develop banking-focused AI solutions for use cases such as customer servicing, document intelligence, lending support, credit assessment, fraud detection, KYC/AML support, compliance assistance, and operations automation. Use Azure OpenAI, Azure AI Foundry, Azure AI Services, Azure AI Search, Azure Machine Learning, Azure Functions, Azure DevOps, and related Azure services to build and deploy enterprise AI applications. Implement AI agents and orchestration workflows using frameworks such as Microsoft Agent Framework, LangGraph, LangChain, CrewAI, and related tools. Support data preprocessing, prompt engineering, vector indexing, retrieval workflows, model integration, testing, evaluation, observability, and performance tuning. Follow secure coding, Responsible AI, AI governance, model validation, documentation, and compliance practices while developing AI solutions. Participate in agile delivery ceremonies, sprint planning, code reviews, defect resolution, deployment support, and production monitoring activities. Create technical documentation, reusable components, solution notes, and implementation guides for AI and Agentic AI solutions. Stay updated with emerging GenAI, Agentic AI, LLMOps, Azure AI, cloud AI services, and software engineering practices relevant to Banking. Present technical progress, demos, solution components, and development outcomes to internal stakeholders and client teams. Support junior developers and analysts through knowledge sharing, code walkthroughs, and hands-on guidance. Skills and Attributes: Professional Experience 4–8 years of experience in Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Data Science, or AI application development, with hands-on experience in building and deploying AI solutions. Experience working on AI / analytics / software engineering projects within the Banking domain is preferred. Good hands-on exposure to developing LLM-based applications, RAG solutions, AI agents, APIs, cloud-native components, and production-ready AI workflows. Experience working in agile delivery teams and collaborating with architects, managers, data scientists, engineers, and business stakeholders. Educational Background Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Statistics, or a related quantitative field. Certifications in Azure AI, Azure Fundamentals, Generative AI, Machine Learning, Cloud Technologies, or Agentic AI platforms are preferred. Technical Skills Agentic AI & Generative AI Hands-on experience with Agentic AI, AI agents, RAG, Agentic RAG, LLM applications, prompt engineering, AI copilots, workflow automation, model evaluation, and enterprise GenAI development Microsoft Azure AI Ecosystem (Mandatory) Practical experience with Azure OpenAI, Azure AI Foundry, Azure AI Services, Azure AI Search, Azure Machine Learning, Azure Functions, Azure DevOps, and Azure-based deployment patterns. Agentic AI Frameworks Development experience with AI agent and orchestration frameworks such as Microsoft Agent Framework, LangGraph, LangChain, CrewAI, and related platforms. AI/ML & Data Science Good understanding of Machine Learning, Deep Learning, NLP, Generative AI, predictive analytics, data preprocessing, feature engineering, model development, evaluation, and monitoring. Banking Expertise Understanding of Banking processes such as customer onboarding, KYC/AML, lending, credit risk, fraud detection, regulatory compliance, customer service, operations, and risk management. Programming & Cloud Strong proficiency in Python and SQL, with exposure to PyTorch or TensorFlow, mandatory Azure experience, and basic knowledge of other cloud platforms such as AWS Bedrock or GCP Vertex AI. Software Engineering & AI Operations Experience with API development, microservices, CI/CD pipelines, Git, Agile methodologies, MLOps, LLMOps, testing, debugging, and enterprise AI deployment practices. Product & Solution Development Good understanding of the AI solution lifecycle including requirement analysis, design, development, testing, deployment, monitoring, documentation, security, and responsible AI practices. Soft Skills Good communication, collaboration, and stakeholder management skills. Ability to understand business problems and convert them into AI, Agentic AI, and analytics development tasks. Strong problem-solving mindset with attention to quality, documentation, and delivery timelines. Ability to work effectively in agile teams and collaborate with cross-functional technology and business teams. Willingness to learn emerging AI technologies and contribute to reusable assets, accelerators, and best practices. Key Responsibilities Develop Agentic AI, Generative AI, RAG, AI Copilot, and LLM-powered solutions for Banking clients using Azure AI ecosystem and modern AI frameworks. Build and integrate AI agents, workflows, APIs, prompts, vector search, and orchestration components using Azure OpenAI, Azure AI Foundry, LangGraph, LangChain and Microsoft Agent Framework. Support end-to-end solution delivery including requirement analysis, development, testing, deployment, documentation, monitoring, and production support. Collaborate with architects, managers, data scientists, engineers, and business teams to translate banking use cases into scalable AI solutions. Follow Responsible AI, AI governance, security, coding standards, model evaluation, and LLMOps practices during solution development. Contribute to demos, reusable components, technical documentation, code reviews, agile delivery, and continuous improvement of AI development practices.