Service Delivery Center, AI & Data, Machine Learning Engineer; MLE - Senior

Position: Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior

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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 Lang Chain, Auto Gen, 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:
  Lang Chain, Auto Gen, CrewAI, or similar multi‑agent orchestration tools
• Vector databases:
  Pinecone, Weaviate, or Chroma for semantic search at scale
• Cloud platforms: AWS Sage Maker, 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
• Experience with real‑time streaming architectures (Kafka, Flink)
• Contributions to open‑source AI projects
• Good written and verbal communication skills
• A willingness and ability to travel at 0%‑25%
• Valid driver’s license in the US
• Valid passport

Ideally, you’ll also have

• Certification in any database management system, reporting or data visualization, or programming/statistical language
• Working knowledge or certifications in cloud technologies such as Snowflake, Databricks, AWS, or Azure
• Experience with generative AI models and techniques, including GANs and Transformers
• Understanding of the ethical implications of generative AI and commitment to responsible…