We are seeking someone to join our AI Development Platform (AIDP) team as a Senior AI Platform Engineering Specialist in Architecture and Modernization to help build a firmwide AI Development Platform and drive adoption of AI capabilities throughout the enterprise. The ideal candidate is a seasoned platform engineer with deep hands‑on experience building and operating large‑scale, cloud‑native platforms on Kubernetes, with strong expertise in API‑driven and REST‑based architectures, data‑intensive systems, and enterprise‑grade service platforms. They bring proven experience delivering Generative AI and LLM‑powered solutions, including agentic systems, orchestration frameworks, and evaluation or benchmarking pipelines, and are comfortable working across the full GenAI lifecycle—from development to production operations. This individual demonstrates a strong platform mindset, excels at building reusable and scalable capabilities, and is passionate about leveraging AI to accelerate developer productivity, improve platform quality, and drive meaningful product and technical innovation across the enterprise. What you’ll do in the role: Design and build a firmwide AI development and evaluation platform with a strong focus on enterprise‑scale GenAI benchmarking, assurance, and governance. Develop self‑service tooling, SDKs, and APIs to enable teams to build, evaluate, and deploy GenAI applications efficiently and safely. Build reusable, scalable platform components for GenAI and agentic systems, including orchestration, evaluation pipelines, and model lifecycle workflows. Lead the implementation of container‑native GenAI workloads on Kubernetes / OpenShift using GitOps‑driven deployment patterns. Integrate and operate GenAI ecosystem components including LLMs, vector databases, embeddings, and agent frameworks. Drive key architecture, product, and design decisions across security, authentication, observability, scalability, and reliability. Establish platform best practices for GenAI evaluations, agentic systems, ModelOps / LLMOps, and production operations. Collaborate closely with engineers, data scientists, security, and product teams to accelerate safe enterprise adoption of GenAI. What you’ll bring to the role: 8+ years of strong hands‑on software engineering experience, preferably in Python (FastAPI, Flask), building large‑scale, cloud‑native platforms. Deep experience designing and operating Kubernetes / OpenShift workloads using Helm, Customize, container registries, and GitOps practices. Hands‑on experience building GenAI and LLM‑based applications, including agentic orchestration, embeddings, evaluation workflows, and fine‑tuning. Strong understanding of microservices, RESTful API design, asynchronous and concurrent programming, and performance‑oriented systems. Solid foundation in data engineering principles including SQL/NoSQL stores, Kafka, Redis, vector databases, and state management at scale. Proficiency in DevOps, CI/CD, observability (OpenTelemetry, Prometheus, Grafana), and SRE‑inspired operational practices. Strong working knowledge of security‑first design, OAuth2, secure coding practices, and enterprise‑grade platform controls. Bachelor’s or master’s degree in computer science or a related field, or equivalent practical experience, with excellent communication and collaboration skills. All our positions are located in Montreal, Quebec. We offer a hybrid work environment, combining remote work and attendance in the office. Knowledge of French and English is required. Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents. #J-18808-Ljbffr