OPT AI Platform Engineer Jobs
AI Platform Engineer jobs are among the most OPT-friendly roles in tech right now, with strong demand from employers already set up to sponsor H-1B visas. Most positions require a master's degree in computer science or a related field, which aligns well with the STEM OPT extension that gives you 36 months of authorized work.
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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).
See all 33+ OPT AI Platform Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT AI Platform Engineer Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as an AI Platform Engineer
Target companies with active H-1B filing history
Employers who regularly file H-1B petitions are far more likely to understand OPT and sponsor you after your authorization period ends. Prioritize companies with engineering teams of 50 or more, where immigration infrastructure already exists.
Emphasize your ML infrastructure experience up front
Hiring managers for AI Platform roles care most about experience with model serving, MLflow, Kubeflow, or similar tooling. Lead with specific systems you have built or maintained, not just the languages or frameworks you know.
Apply during STEM OPT, not at the end of it
Starting your search six to nine months before your OPT expires gives employers realistic runway to prepare an H-1B petition. Waiting until the final months signals urgency that makes risk-averse hiring managers hesitate on sponsorship conversations.
Get your STEM OPT extension filed before the job search
Confirm your I-983 training plan is in order and your extension EAD has been applied for before you start interviewing. Employers will ask about your timeline, and a concrete answer builds confidence that hiring you carries no immediate risk.
Clarify the role qualifies as a specialty occupation
AI Platform Engineer positions almost universally require a bachelor's degree or higher in a specific technical field, which satisfies the specialty occupation standard. Confirm this with your DSO so you can speak to it confidently when the topic arises with employers.
Use Migrate Mate to find OPT-friendly AI Platform roles
Migrate Mate filters for employers who are actively open to OPT candidates, so you spend less time cold-applying to companies that will reject you at the visa question. Browse current AI Platform Engineer listings to shortlist realistic targets before you reach out.
AI Platform Engineer OPT: Frequently Asked Questions
Do AI Platform Engineer jobs qualify for the STEM OPT extension?
Yes, in most cases. AI Platform Engineer roles fall under CIP codes in computer science or electrical engineering, which are on the STEM Designated Degree Program list. Your degree field, not the job title, determines STEM OPT eligibility, so confirm with your DSO that your program qualifies. Once confirmed, you get 24 additional months on top of your initial 12-month OPT period.
How does the practical training requirement work for AI Platform Engineer positions?
Your job must be directly related to your degree field. For AI Platform Engineers, roles involving model deployment, infrastructure automation, distributed systems, or data pipeline architecture almost always satisfy this requirement given their connection to computer science and engineering coursework. Document this connection carefully in your I-983 training plan, which your employer must sign and your DSO must approve before your STEM OPT extension is granted.
Will employers sponsor an H-1B visa after my OPT period ends?
Many do, but it varies by company size, budget, and hiring philosophy. Large tech companies and well-funded AI startups are the most consistent sponsors because they have legal teams set up to handle immigration. AI Platform Engineer is a high-demand, specialized role, which strengthens your negotiating position. Start the H-1B conversation early in the hiring process rather than after an offer is made.
Can I work as a contractor or on a project basis while on OPT?
Yes, but with conditions. OPT allows self-employment and contract work as long as the work is directly related to your degree. For AI Platform Engineers, contract engagements in machine learning infrastructure or cloud platform development typically qualify. You must work at least 20 hours per week to remain in valid OPT status, and unemployment gaps beyond 90 days cumulatively can jeopardize your authorization.
Where can I find AI Platform Engineer jobs that accept OPT candidates?
Migrate Mate is built specifically for this. The platform surfaces AI Platform Engineer roles from employers who are open to OPT candidates and have a track record of sponsoring visas, so you can filter out companies that will reject your application at the authorization step. Browse current listings on Migrate Mate to identify realistic targets based on your graduation date and OPT timeline.