Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management, and wealth management services. The role involves leading the evolution of the firm's real-time fraud screening platform by integrating machine learning and Generative AI capabilities while providing technical leadership to an Agile squad.
Responsibilities:
- Lead design and development of high-performance Java or Scala microservices for real-time fraud detection
- Architect scalable solutions incorporating LLMs, vector search, prompt engineering, and RAG patterns
- Integrate GenAI capabilities such as alert explanation, anomaly summarization, synthetic data generation, and automation
- Drive cloud-ready and containerized development using Docker and Kubernetes
- Partner with data science teams to productionize machine learning and GenAI models
- Implement APIs for AI inference, model orchestration, and governance
- Ensure compliance with responsible AI, model risk, and data privacy standards
- Guide engineering teams in CI or CD, DevOps tooling, code quality, and observability
- Mentor junior engineers and promote innovation and continuous learning
- Collaborate with fraud analysts, reporting teams, and data governance stakeholders
- Contribute to the target-state architecture for fraud detection platforms
- Evaluate new AI technologies and frameworks for enterprise adoption
- Support roadmap planning and long-term strategic decisions