Job description

You are required to review the Firm’s Mobility Guidelines on careerhub/ prior to submitting your application to ensure you understand and abide by your obligations under the Firm policy. JOB LEVEL Vice President TIER P4 Company Profile 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. Team Profile 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. Role Profile 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. Key Responsibilities Platform and Application Engineering • 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. AI and ML Integration • 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. Technical Leadership • 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. Architecture and Strategy • 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. Required Skills and Experience Core Engineering • 10 plus 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. Generative AI and Machine Learning • 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. Cloud and DevOps • 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. Soft Skills • 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. Preferred 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. WHAT YOU CAN EXPECT FROM MORGAN STANLEY: 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 morganstanley.com 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). Internal Applicants Internal mobility can be a way to grow your career and realize your professional potential. Typically, you must be in your position for at least 18 months and performing satisfactorily before applying for another job at the Firm. Internal applicants can find out more regarding career navigation, mobility guidelines and policy on our employee portal by clicking here.

Requirements

Must-haves

You are required to review the Firm’s Mobility Guidelines on careerhub/ prior to submitting your application to ensure you understand and abide by your obligations under the Firm policy.
Vice President
Company Profile
Team Profile
Our work includes building real-time, batch, and analytical systems, integrating vendor solutions, and driving adoption of Generative AI across fraud workflows.
Role Profile
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.
Platform and Application Engineering
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.
AI and ML Integration
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.
Technical Leadership

Nice-to-haves

Familiarity with MLOps, feature stores, and model monitoring is a plus.
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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aijavamachine learningagiledockerkubernetesmlsqlazurepythonscrumapi

Platform: eightfold
Effort: medium