In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Cloud & Infra Engineering Manager position at the Vice President level, which is part of the job family responsible for managing and optimizing technical infrastructure and ensuring the seamless operation of IT systems to support business needs effectively.Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on.Role Profile:Morgan Stanley has been at the forefront of the AI journey with applications such as Genome that use AI to provide better, personalized advice to our clients. Generative AI provides further unique opportunities to provide new capabilities to the firm’s internal users as well as our clients. This role is for a senior platform engineer who will help build a firmwide AI Development Platform and drive adoption of AI capabilities throughout the enterprise. The ideal candidate will have strong hands-on experience of building software platforms on Kubernetes, API based development, REST framework, data engineering, and large-scale API Gateway environments etc. Knowledge of AIML and hands-on experience implementing solutions using Generative AI are also preferable. The candidate will have a strong passion for using AI to increase productivity as well as help generate new ideas for product & technical improvements.What you’ll do in the role:Develop tooling and self-service capabilities for deploying AI solutions for the firm. Collaborate with other developers to enhance the developer experience when building and deploying AI applications.Have a platform mindset and build common, reusable solutions to scale Generative AI use cases using pre-trained models as well as fine-tuned models.Collaborate with product manager, other tech leads, junior staff and other stakeholders to analyze requirements, translate them into technical specification and architecture documentation.Design scalable, robust, secure, and flexible architecture of components of the AI development platform.Leverage Kubernetes/OpenShift to develop modern containerized workloads.Leverage container registries like JFrog artifactory, container packaging/configuration management technologies like Helm & Kustomize, and GitOps deployment methods to orchestrate, manage and deploy these workloads.Integrate with capabilities such as large-scale vector stores for embeddings.Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain.Analyze, investigate, and implement GenAI solutions focusing on Agentic Orchestration and Agent Builder frameworks.Contribute to major design decisions and product selection for building Generative AI solutions. Inclusive of app authentication, service communication, state externalization, container layering strategy and immutability.Ensure AI platform are reliable, scalable, and operational; (e.g. blueprints for upgrade/release strategies (E.g. Blue/Green); logging/monitoring/metrics; automation of system management tasks)Participate in all team’s Agile/ Scrum ceremonies.What you’ll bring to the role:8+ years of experience in software engineering, design, and developmentExperience architecting distributed systems.Experience building AI applications, preferably Generative AI and LLM based apps.Strong hands-on Application Development background in at least one prominent programming language, preferably Python Flask or FAST Api.Broad understanding of data engineering (SQL, NoSQL, Big Data, Kafka, Redis), data governance, data privacy and security.Experience in development, management, and deployment of Kubernetes workloads, preferably on OpenShift.Experience with designing, developing, and managing RESTful services for large-scale enterprise solutions.Hands-on experience with multiprocessing, multithreading, asynchronous I/O, performance profiling in at least one prominent programming language, preferably python.Practitioner of unit testing, performance testing and BDD/acceptance testing.Proficiency with Open Telemetry tools including Grafana, Loki, Prometheus, and Cortex.Demonstrated experience in DevOps, understanding of CI/CD (Jenkins) and GitOps.Ability to articulate technical concepts effectively to diverse audiences.Strong desire and ability to influence development teams and help them adopt AI.Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations.Understanding of deep learning, understanding of Machine Learning frameworks such as TensorFlow or PyTorch.Understanding of Information Security, Secure coding practices.Experience in building cloud and container native applications.Excellent communication skills.WHAT YOU CAN EXPECT FROM MORGAN STANLEY:We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 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 [hour/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).
