Lead GenAI Java Developer - VP
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Benefits offered by this job
Job summary
Qualifications
- 10+ years of Java engineering experience with performance knowledge.
- Experience in microservices and distributed systems.
- Understanding of relational databases like Sybase or Oracle.
Responsibilities
- Lead design and development of Java microservices for fraud detection.
- Partner with data science teams for implementing ML models.
- Guide teams in CI/CD, DevOps, code quality practices.
Skills
Education
Tools
Job description
Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management, and wealth management services. The firm’s employees serve clients worldwide including corporations, governments, and individuals from more than 1,200 offices in 43 countries.
The Fraud Technology group within NFRT delivers solutions to detect, prevent, and analyze fraud across the enterprise. We partner with cybersecurity, fraud analytics, compliance, legal, data governance, and operations teams to design scalable and intelligent fraud detection platforms.
Our work includes building real‑time, batch, and analytical systems, integrating vendor solutions, and driving adoption of Generative AI across fraud workflows.
As a Vice President – Java Engineering and Generative AI, you will lead the evolution of Morgan Stanley’s real‑time fraud screening platform, integrating machine learning and Generative AI capabilities.
You will collaborate with architects, analytics teams, and data governance partners while providing technical leadership to an Agile squad. The role includes shaping engineering best practices, mentoring developers, driving solution design, and championing GenAI adoption across Fraud Technology.
- 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.
- 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.
- Prompt engineering and RAG.
- Vector databases such as Pinecone, FAISS, Weaviate, Elastic Vector Search.
- Model deployment and inference using tools such as Transformers, LangChain, LlamaIndex.
- Hands‑on experience with Python for ML or AI workflows.
- Familiarity with MLOps, feature stores, and model monitoring is a plus.
- Experience building cloud‑ready applications and containerized deployments using Docker and Kubernetes.
- Knowledge of CI or 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.
- 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.
At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values – putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back – aren’t just beliefs, they guide the decisions we make every day to do what’s best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries.
At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work‑life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Expected base pay rates for the role will be between $150,000 and $210,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long‑term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley’s goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
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.
Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).
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