AI Platform Engineer Architect

Morgan Stanley

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$155,000–$215,000 / yr
Posted
4 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $194k
This role $185k
$132k most similar roles pay here $246k

This role pays less than 52% of similar roles. Most pay $156,956–$231,150 — the shaded band above. At the midpoint, this role pays about $185k versus about $194k for comparable roles.

Based on 240 similar postings.

Employer

About Morgan Stanley

Morgan Stanley is a global financial services firm providing investment banking, securities, wealth management, and investment management services to corporations, governments, institutions, and individuals. Industry: Investment Banking & Financial Services

Morgan Stanley currently has 39 open roles on FindRole.

Listed pay typically runs $150,000–$210,000 across 34 roles with salary data.

Most-posted roles

View all roles at Morgan Stanley

At a glance

TL;DR · AI Platform Engineer Architect

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The AI Platform Engineer / Architect - VP joins the Technology division to build a firmwide Artificial Intelligence Development Platform designed to drive consistency, security, and innovation across the enterprise. This role involves developing tooling and self-service capabilities for deploying AI solutions, creating Terraform modules for secure cloud architecture, and building reusable components for Generative AI use cases. The engineer will work with Kubernetes, OpenShift, Python (Flask or FastAPI), and REST frameworks while integrating large-scale vector stores for embeddings. Key responsibilities include authoring best practices for the Generative AI ecosystem, including LangChain and various models like GPT and Llama, and implementing Agentic Orchestration. Technical requirements include experience with AWS, Azure, or GCP, SQL/NoSQL databases, Kafka, Redis, and CI/CD pipelines via Jenkins to ensure scalable, reliable, and secure infrastructure for advanced machine learning applications.

Skills

Python Kubernetes OpenShift AWS Azure GCP Terraform Generative AI LangChain REST SQL NoSQL Kafka Redis CI/CD Jenkins GitOps Prometheus Grafana Loki Cortex ML Ops SRE

What you'll do

  • Develop tooling and self-service capabilities for deploying AI solutions using Kubernetes, Python, and REST frameworks.
  • Create Terraform modules and cloud architecture to enable secure, large-scale deployment of AI services.
  • Build reusable platform components to scale Generative AI use cases using pre-trained and fine-tuned models.
  • Integrate large-scale vector stores for embeddings and manage containerized workloads on OpenShift.
  • Author best practices and technical documentation regarding the Generative AI ecosystem, including LangChain and various LLMs.
  • Implement Agentic Orchestration and Agent Builder frameworks to develop automated GenAI solutions.
  • Document architecture decision records covering authentication, service communication, and deployment strategies.
  • Ensure platform reliability through monitoring, logging, and automated management tasks like Blue/Green deployment strategies.

What we're looking for

  • Bachelor's or Master's degree in Computer Science or related field, or equivalent job experience.
  • 8+ years of experience in software engineering, design and development.
  • Strong application development background in a prominent programming language, preferably Python Flask or FastAPI.
  • Experience developing and managing RESTful services for large-scale enterprise solutions.
  • Experience deploying applications on Azure, AWS, and/or GCP using Terraform (IaC).
  • Experience with Kubernetes workloads, preferably on OpenShift.
  • Demonstrated experience in DevOps, including CI/CD (Jenkins) and GitOps.
  • Knowledge of Generative AI, LLM based apps, and Agentic Orchestration frameworks like LangChain or LangGraph (preferred).

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