11 days ago

AI Cloud Solution Engineer Director

Morgan Stanley

On Site
Full Time
$190,000
Bengaluru, Karnataka, India
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Job Overview

Job TitleAI Cloud Solution Engineer Director
Job TypeFull Time
Offered Salary$190,000
LocationBengaluru, Karnataka, India
Map of Bengaluru, Karnataka, India

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Job Description

About the Role

We’re seeking an AI Cloud Solution Engineer to join our Enterprise Technology team within Architecture & Modernization. You will help build a firmwide AI Development Platform to foster AI capability adoption across the enterprise. The ideal candidate possesses strong hands-on experience in building secure cloud services, software platforms, and API-based development. Knowledge of LLM models and practical experience with Generative AI solutions is also preferred. You should have a strong passion for leveraging AI to boost productivity and generate innovative product ideas.

This role demands a robust blend of software development and cloud infrastructure expertise. The successful candidate will demonstrate technical leadership and a proven track record of developing and driving innovative solutions.

About Technology at Morgan Stanley

In the Technology division, we harness innovation to create the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.

Director Position Overview

This is a Director position responsible for developing and maintaining software solutions that support business needs.

About Morgan Stanley

Since 1935, Morgan Stanley has been a global leader in financial services, consistently evolving and innovating to better serve our clients and communities in over 40 countries worldwide.

What You’ll Do In The Role

  • Collaborate with engineers and teams to onboard new cloud services.
  • Architect new cloud solutions for emerging use cases, adhering to Morgan Stanley's security standards.
  • Build Proofs of Concept (POCs) and example code enabling developers to access Generative AI models via standard APIs.
  • Apply an application developer mindset to build common, reusable solutions for scaling Generative AI use cases.
  • Contribute to significant design decisions and production deployments.
  • Deploy resources to the cloud using Terraform and CI/CD pipelines.
  • Design and implement highly scalable architectures for enterprise applications.
  • Develop in Python; proficiency in additional languages is a plus.
  • Create code samples for baseline implementations.
  • Effectively articulate technical concepts to diverse audiences.

What You’ll Bring To The Role

  • Minimum 6+ years of relevant experience.
  • Experience building applications using AI development services on cloud platforms like Azure (Open AI, AI Foundry, Search, Cognitive Services), AWS (Bedrock, SageMaker), or Google Cloud (Vertex AI).
  • Hands-on experience managing code in repositories such as Bitbucket and GitHub.
  • Broad understanding of data engineering (SQL, NoSQL, Big Data), data governance, data privacy, and security.
  • Experience in large, regulated industries (e.g., Financial Services, Insurance).
  • Proven experience building AI applications, preferably Generative AI and LLM-based.
  • Proficiency with Python, particularly API development using Flask or FastAPI.
  • Understanding of Kubernetes and deployment best practices (e.g., Helm, GitOps).
  • Bachelor's or Master's degree in Computer Science or related field, or equivalent experience.
  • Experience in enterprise software engineering, design, and development.
  • Experience implementing enterprise architecture on at least one major cloud provider (Azure, AWS, GCP).
  • Relevant Microsoft, AWS, GCP, or Terraform certifications are a plus.
  • Demonstrated ability to work effectively in a global organization across different time zones.
  • Understanding of information security and secure coding practices.
  • Strong documentation and organizational skills.

What You Can Expect From Morgan Stanley

At Morgan Stanley, we raise, manage, and allocate capital for our clients, helping them achieve their goals. We’ve been doing this distinctively for 90 years. Our core values—putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back—guide our daily decisions to best serve our clients, communities, and over 80,000 employees across 1,200 offices in 42 countries. At Morgan Stanley, you’ll have the opportunity to collaborate with top talent in a supportive and empowering environment. Our teams are composed of relentless collaborators and creative thinkers, fueled by diverse backgrounds and experiences. We are committed to supporting our employees and their families throughout their work-life journey, offering industry-leading benefits and perks. We also provide ample opportunities for career growth for those who demonstrate passion and grit.

To explore our global offices, please visit: https://www.morganstanley.com/about-us/global-offices

Morgan Stanley is an equal opportunity employer committed to fostering a diverse workforce. Our recruiting efforts prioritize inclusion, ensuring individuals are hired, developed, and advanced based on their skills and talents.

Our workforce mirrors the global communities we serve, bringing together a wide array of backgrounds, talents, perspectives, and experiences. For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.

Key skills/competency

  • AI Cloud Solution Engineering
  • Generative AI
  • LLM Models
  • Cloud Architecture
  • Software Development
  • API Development
  • Python
  • Terraform
  • CI/CD
  • Enterprise Architecture

Tags:

AI
Cloud Solutions
Solution Engineer
Director
Software Engineering
Generative AI
LLM
Cloud Architecture
Python
API Development
Terraform
CI/CD
Enterprise Architecture
Morgan Stanley
Financial Services

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How to Get Hired at Morgan Stanley

  • Tailor your resume: Highlight AI, cloud, and Python experience.
  • Showcase leadership: Emphasize technical direction and innovation.
  • Demonstrate cloud expertise: Detail Azure, AWS, or GCP project experience.
  • Quantify achievements: Use metrics to show impact of your solutions.
  • Prepare for technical interviews: Practice coding and system design questions.

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