Senior AI Development Platform Engineer - VP

Morgan Stanley-posted 12 days ago

Full-time • Mid Level

New York, NY

5,001-10,000 employees

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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.

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.

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.
Understanding of OAuth 2.0 protocol for secure authorization.
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.
Knowledge of DevOps and Agile practices.
Excellent communication skills.
10+ years of experience in software engineering, design, and development
5+ years of experience architecting distributed systems.

Strong understanding and experience designing and building software following cloud-native architecture with microservices, Kubernetes, docker, kafka, etc.
Good knowledge of Microservice based architecture, industry standards, for both public and private cloud.
Good understanding of modern Application configuration techniques.
Hands on experience with Cloud Application Deployment patterns like Blue/Green.
Good understanding of State sharing between scalable cloud components (Kafka, dynamic distributed caching).
Good knowledge of various DB engines (SQL, Redis, Kafka, etc) for cloud app storage.
Experience building AI applications, preferably Generative AI and LLM based apps.
Deep understanding of AI agents, Agentic Orchestration, Multi-Agent Workflow Automation, along with hands-on experience in Agent Builder frameworks such Lang Chain and Lang Graph.
Experience working with Generative AI development, embeddings, fine tuning of Generative AI models.
Understanding of ModelOps/ ML Ops/ LLM Op.
Understanding of SRE techniques.
Understanding of Responsible AI, AI Ethics .
Understanding of Information Security, Secure coding practices .
1+ year of experience building AI applications, preferably Generative AI and LLM based apps.

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