STEM OPT AI Platform Engineer Jobs
AI Platform Engineer roles sit squarely within STEM-designated fields, making them a strong fit for the 24-month STEM OPT extension. Your employer must be enrolled in E-Verify and sign your I-983 training plan. Eligible degrees typically include computer science, electrical engineering, and related CIP-coded disciplines.
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Get Access To All JobsINTRODUCTION
Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.
This role is for a platform engineering specialist who will help build a firmwide AI Development Platform and drive adoption of AI capabilities throughout the enterprise. We have multiple focus areas across the platform and are looking for energetic, multi-disciplinary candidates who are eager to contribute to providing scalable, secure, enterprise-wide solutions for the firm.
The ideal candidate will have strong hands-on experience building software platforms on any combination of the following platforms - Kubernetes, Cloud (AWS, Azure, and/or Google), 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 great communication skills, a team-based mentality and a strong passion for using AI to increase productivity as well as help generate new ideas for product & technical improvements.
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.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
ROLE AND RESPONSIBILITIES
What you'll do in the role:
Below is a sample of potential responsibilities depending on product / focus area
- Build and enhance Python-based microservices (Flask, Fast API) by empowering the AI platform.
- Extend and maintain connectors for external LLM providers: OpenAI, Azure AI Foundry, and AWS Bedrock.
- Build Helm charts, parameterized templates, and multi-env promotion workflows to develop modern containerized workloads.
- Develop tooling and self-service capabilities for deploying AI solutions for the firm leveraging Kubernetes/OpenShift, Python, authentication solutions, APIs, REST framework, etc.
- 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.
- 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.
- Author and publish architecture decision records to capture 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 is 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.
- Participate in team's oncall rotation in build/run team model.
BASIC QUALIFICATIONS
What you'll bring to the role:
- Bachelor's or master's degree in computer science or related field, or equivalent job experience.
- 5 years of experience in software engineering, design and development.
- 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.
- Experience deploying applications on Azure, AWS, and/or GCP using IaC (Terraform).
- Hands-on experience with multiprocessing, multithreading, asynchronous I/O, performance profiling in at least one prominent programming language, preferably python.
- Ability to articulate technical concepts effectively to diverse audiences.
- Excellent communication skills.
- Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations.
- Demonstrated experience in DevOps, understanding of CI/CD (Jenkins) and GitOps.
- Knowledge of DevOps and Agile practices.
PREFERRED QUALIFICATIONS
Nice to have:
- 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.
- 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.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY
We have a track record of innovation and passion for unlocking new opportunities, we help our clients raise, manage and allocate capital. We do this by offering a wide range of investment banking, securities, wealth management and asset management services.
All that we do at Morgan Stanley is driven by our five core values: do the right thing, put clients first, lead with exceptional ideas, commit to diversity and inclusion, and give back. These aren't just beliefs, they guide the decisions we make every day, ensuring we do what's best for our clients, communities and more than 80,000 employees around the world. And at the core of our success are the people who drive it - relentless collaborators and creative thinkers who are fueled by diverse thinking and experiences.
Wherever you are in our 1,200 global offices, you'll have the opportunity to work alongside the best and the brightest in an environment where you are empowered to achieve your full potential. 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.
At Morgan Stanley Montreal, we support the Firm's global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, data.
EEO STATEMENT
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).
INTRODUCTION
Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.
This role is for a platform engineering specialist who will help build a firmwide AI Development Platform and drive adoption of AI capabilities throughout the enterprise. We have multiple focus areas across the platform and are looking for energetic, multi-disciplinary candidates who are eager to contribute to providing scalable, secure, enterprise-wide solutions for the firm.
The ideal candidate will have strong hands-on experience building software platforms on any combination of the following platforms - Kubernetes, Cloud (AWS, Azure, and/or Google), 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 great communication skills, a team-based mentality and a strong passion for using AI to increase productivity as well as help generate new ideas for product & technical improvements.
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.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
ROLE AND RESPONSIBILITIES
What you'll do in the role:
Below is a sample of potential responsibilities depending on product / focus area
- Build and enhance Python-based microservices (Flask, Fast API) by empowering the AI platform.
- Extend and maintain connectors for external LLM providers: OpenAI, Azure AI Foundry, and AWS Bedrock.
- Build Helm charts, parameterized templates, and multi-env promotion workflows to develop modern containerized workloads.
- Develop tooling and self-service capabilities for deploying AI solutions for the firm leveraging Kubernetes/OpenShift, Python, authentication solutions, APIs, REST framework, etc.
- 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.
- 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.
- Author and publish architecture decision records to capture 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 is 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.
- Participate in team's oncall rotation in build/run team model.
BASIC QUALIFICATIONS
What you'll bring to the role:
- Bachelor's or master's degree in computer science or related field, or equivalent job experience.
- 5 years of experience in software engineering, design and development.
- 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.
- Experience deploying applications on Azure, AWS, and/or GCP using IaC (Terraform).
- Hands-on experience with multiprocessing, multithreading, asynchronous I/O, performance profiling in at least one prominent programming language, preferably python.
- Ability to articulate technical concepts effectively to diverse audiences.
- Excellent communication skills.
- Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations.
- Demonstrated experience in DevOps, understanding of CI/CD (Jenkins) and GitOps.
- Knowledge of DevOps and Agile practices.
PREFERRED QUALIFICATIONS
Nice to have:
- 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.
- 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.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY
We have a track record of innovation and passion for unlocking new opportunities, we help our clients raise, manage and allocate capital. We do this by offering a wide range of investment banking, securities, wealth management and asset management services.
All that we do at Morgan Stanley is driven by our five core values: do the right thing, put clients first, lead with exceptional ideas, commit to diversity and inclusion, and give back. These aren't just beliefs, they guide the decisions we make every day, ensuring we do what's best for our clients, communities and more than 80,000 employees around the world. And at the core of our success are the people who drive it - relentless collaborators and creative thinkers who are fueled by diverse thinking and experiences.
Wherever you are in our 1,200 global offices, you'll have the opportunity to work alongside the best and the brightest in an environment where you are empowered to achieve your full potential. 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.
At Morgan Stanley Montreal, we support the Firm's global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, data.
EEO STATEMENT
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).
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Get Access To All JobsTips for Finding STEM OPT Authorization as an AI Platform Engineer
Verify your degree qualifies by CIP code
Not every computer science or engineering degree automatically qualifies. Cross-reference your degree's CIP code against the STEM Designated Degree Program list that USCIS recognizes before you apply, so there are no surprises when your DSO files the extension.
Check E-Verify enrollment before accepting offers
An employer that isn't enrolled in E-Verify cannot legally employ you on STEM OPT. Search the E-Verify employer search tool by company name before you start the offer negotiation, not after you've signed.
Build a portfolio that proves production-scale work
AI Platform Engineer roles require demonstrating infrastructure experience at scale, not just model experimentation. Include Kubernetes cluster management, MLOps pipelines, or distributed training setups in your portfolio so hiring managers can map your work to the I-983 training plan objectives.
Use O*NET to align your training plan tasks
The I-983 requires concrete, role-specific training goals. Pull the task and knowledge requirements directly from the O*NET occupation profile for AI and ML engineers to draft training objectives your employer can sign off on without back-and-forth.
Target employers with existing PERM or H-1B filing history
Companies that have filed PERM labor certifications or H-1B petitions for engineering roles already have compliant processes for STEM OPT. Use Migrate Mate to filter AI Platform Engineer roles by employers with that verified DOL filing history.
File your STEM OPT extension 90 days before OPT expires
USCIS processing can run several months, and your filing window opens 90 days before your current EAD expires. Submitting late risks an authorization gap that pauses your employment, which is especially disruptive mid-sprint on a platform infrastructure project.
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Find AI Platform Engineer JobsFrequently Asked Questions
Does an AI Platform Engineer role qualify for the STEM OPT extension?
Yes, provided your employer is enrolled in E-Verify and your degree falls under a STEM-designated CIP code. Roles focused on building and maintaining ML infrastructure, distributed compute systems, or AI deployment pipelines align directly with STEM-designated fields such as computer science, computer engineering, and electrical engineering. Confirm your specific degree CIP code against the current STEM Designated Degree Program list before filing.
What should the I-983 training plan cover for this role?
Your I-983 must describe concrete, role-specific learning goals tied to your STEM degree, not generic job duties. For an AI Platform Engineer, that means training objectives around areas like distributed training infrastructure, MLOps pipeline design, container orchestration, or model serving architecture. Use the O*NET occupation profile for AI and ML engineers to identify task-level language your employer can review and sign. USCIS may audit the plan, so vague entries create risk.
How do I confirm my employer is enrolled in E-Verify?
Use the E-Verify employer search tool, which is publicly available through the E-Verify program, to search by company name or employer identification number before accepting an offer. Enrollment status can change, so verify it after receiving an offer letter, not just during initial research. If an employer is not enrolled, they must complete enrollment before your STEM OPT employment can begin, which can delay your start date.
What happens to my work authorization if my H-1B is selected in the lottery while I'm on STEM OPT?
If your employer files an H-1B petition on your behalf and it's selected in the lottery, the cap-gap rule extends your STEM OPT work authorization automatically through September 30 of that fiscal year, or until USCIS adjudicates your petition, whichever comes later. You don't need to file a new EAD during the cap-gap period, but your employer should confirm they filed before your STEM OPT EAD expired.
Where can I find AI Platform Engineer jobs from employers who support STEM OPT?
Migrate Mate filters AI Platform Engineer roles by employers with verified E-Verify enrollment and DOL filing history, so you're not spending time on companies that can't legally employ STEM OPT students. Searching there narrows your list to employers who have already demonstrated a willingness to sponsor and comply with the documentation requirements your STEM OPT extension demands.
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