Morgan Stanley is hiring a Lead GenAI Java Developer to lead the evolution of our real-time fraud screening platform. You will integrate machine learning and Generative AI capabilities while collaborating with architects, analytics teams, and data governance partners. This role involves providing technical leadership to an Agile squad, shaping engineering best practices, mentoring developers, and championing GenAI adoption across Fraud Technology.
What You'll Do
- 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/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.
What We're Looking For
- 10+ years of hands-on Java engineering experience with strong knowledge of performance, concurrency, and distributed systems.
- Experience with Scala or willingness to learn.
- Strong understanding of microservices, distributed caching, and relational databases such as Sybase, Oracle, or MS SQL.
- Knowledge of messaging or middleware such as Kafka and MQ.
- Practical experience with GenAI technologies including LLMs such as OpenAI, Azure OpenAI, Anthropic.
- Practical experience with prompt engineering and RAG.
- Practical experience with vector databases such as Pinecone, FAISS, Weaviate, Elastic Vector Search.
- Practical experience with model deployment and inference using tools such as Transformers, LangChain, LlamaIndex.
- Hands-on experience with Python for ML or AI workflows.
- Experience building cloud-ready applications and containerized deployments using Docker and Kubernetes.
- Knowledge of CI/CD pipelines, automated testing, and observability tools such as Grafana, Splunk, and Prometheus.
- Strong analytical and problem-solving ability.
- Excellent written and verbal communication skills.
- Ability to work effectively in a global and fast-paced environment.
- Strong stakeholder management and leadership skills.
Nice to Have
- Background in fraud, cybersecurity, risk technology, or financial services.
- Understanding of reactive programming.
- Experience working in Agile or Scrum environments.
- Hands-on experience with distributed systems, event-driven architectures, and API-first design.
- Familiarity with MLOps, feature stores, and model monitoring.
Technical Stack
- Languages: Java, Scala, Python
- Databases: Sybase, Oracle, MS SQL, Pinecone, FAISS, Weaviate, Elastic Vector Search
- Middleware: Kafka, MQ
- AI/ML: OpenAI, Azure OpenAI, Anthropic, Transformers, LangChain, LlamaIndex
- Infrastructure: Docker, Kubernetes, Grafana, Splunk, Prometheus
Team & Environment
You will join an Agile squad within the Fraud Technology group, collaborating closely with architects, data scientists, and business stakeholders.
Benefits & Compensation
- Base compensation of $150,000-$210,000 per year.
- Comprehensive employee benefits and perks.
- Opportunity to move about the business.
Work Mode
This is a global role. Morgan Stanley has employees in 1,200 offices across 42 countries.
Morgan Stanley is committed to putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back. It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
