Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior
EYAbout the role
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
Senior Analyst - Financial Services Organization – AI and Data – Service Delivery Center
EY is the only professional services firm with a separate business unit (“FSO”) that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. This practice also has several Service Delivery Centers that are made up of high-performing US-based resources who work closely with our experienced client-serving professionals to deliver project-based work and managed services to our US-based Financial Services clients. If you have a passion for rallying together to solve the most complex challenges in the financial services industry, come join our dynamic FSO team!
The Opportunity
You’ll architect and deploy production-grade AI agents and multi-agent systems that transform financial services. Working with cutting-edge LLMs and agentic frameworks, you’ll build autonomous systems that process millions of transactions, make intelligent decisions, and continuously learn from real-world financial data. This is your chance to shape how AI reshapes global finance.
What You’ll Do
Build Autonomous Financial AI Systems
- Design and implement multi-agent architectures using LangChain, AutoGen, or CrewAI for complex financial workflows
- Deploy production-ready LLMs fine-tuned for financial domain expertise (loan underwriting, risk assessment, regulatory compliance)
- Create RAG (Retrieval-Augmented Generation) systems that connect AI agents to enterprise knowledge bases and real-time market data
- Implement agentic reasoning systems capable of autonomous decision-making within regulatory boundaries
Scale AI Solutions for Enterprise Impact
- Deploy AI agents serving millions of customers with sub-second latency requirements
- Build robust MLOps pipelines for continuous model improvement and A/B testing
- Implement comprehensive monitoring and observability for autonomous systems
- Optimize inference costs while maintaining performance SLAs
Drive Innovation in Financial AI
- Prototype breakthrough applications: AI-powered trading assistants, autonomous compliance monitors, intelligent fraud detection agents
- Collaborate with financial domain experts to translate complex regulations into AI agent behaviors
- Contribute to EY’s AI research initiatives and patent applications
- Present solutions to C-suite executives at major financial institutions
Technical Requirements
Core Skills (Must-Have)
- 3-5 years of Python programming with production deployment experience
- Hands-on experience with LLMs: GPT-4, Claude, Llama, or similar foundation models
- Agentic AI frameworks: LangChain, AutoGen, CrewAI, or similar multi-agent orchestration tools
- Vector databases: Pinecone, Weaviate, or Chroma for semantic search at scale
- Cloud platforms: AWS SageMaker, Azure OpenAI Service, or Google Vertex AI
- MLOps practices: Model versioning, A/B testing, drift detection, and continuous deployment
Preferred Skills (Nice-to-Have)
- Experience with financial services applications (trading, risk, compliance, or banking)
- Knowledge of prompt engineering and in-context learning optimization
- Familiarity with model fine-tuning techniques (LoRA, QLoRA, PEFT)
- Understanding of AI safety practices and responsible AI frameworks
- E
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