招聘
Platform Engineer - Python/FastAPI/Kubernetes/Terraform/AI - Vice President - Software Engineering

Platform Engineer - Python/FastAPI/Kubernetes/Terraform/AI - Vice President - Software Engineering
Bangalore, India; Mumbai, India
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Learning and development stipend
•Flexible PTO policy
•Remote work flexibility
•Annual team offsites
•Parental leave program
Required Skills
SQL
PyTorch
Apache Spark
Platform Engineer
- Python/FastAPI/Kubernetes/Terraform/AI - Vice President
- Software Engineering
We're seeking someone to join our Enterprise Technology & Services Team as Vice President. This role is for a platform engineer 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.
Architecture & Modernization Drives development of the global firm strategy to define modern architectures and guardrails to reduce legacy debt, while partnering with app dev to accelerate the adoption of modern capabilities
Advisory is responsible for end-to-end process life cycle support for Investment Banking, Global Capital Markets and Research with a focus on efficiency, scale, and time to market. Sales Distribution develops technology for the firm's IED and FID Sales and Distribution business units, creating application synergies across the businesses various platforms
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. This is a Lead Software Engineering position at Vice President level, which is part of the job family
responsible for developing and maintaining software solutions that support business needs.
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.
What you'll do in the role:
- Develop tooling and self-service capabilities for deploying AI solutions for the firm leveraging Kubernetes/Open Shift, Python, authentication solutions, APIs, REST framework, etc
- Develop Terraform modules and Cloud architecture to enable secure AI cloud service deployment and consumption at scale
- 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.> Leverage Kubernetes/Open Shift to develop modern containerized 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
- 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 teams on call rotation in build/run team model
What you'll bring to the role:
- 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.
Required Skills:
- 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 Open Shift.
- 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 Git Ops.
- Knowledge of DevOps and Agile practices.
- At least 8 years' relevant experience would generally be expected to find the skills required for this role
Desired Skills:
- 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 Model Ops/ ML Ops/ LLM Op.
- Understanding of SRE
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. 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. There's also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.
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About Morgan Stanley

Morgan Stanley
PublicA financial services company that offers securities, asset management, and credit services.
10,001+
Employees
New York
Headquarters
Reviews
3.5
4 reviews
Work Life Balance
3.0
Compensation
2.5
Culture
3.2
Career
3.0
Management
3.0
35%
Recommend to a Friend
Pros
Skills evaluation through business plans and projects
Direct access to senior leadership interviews
Conversational interview format
Cons
Automated resume screening system issues
Focus on formatting over qualifications
Compensation concerns and salary expectations
Salary Ranges
11,766 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
1,682 reports
$114,371
total / year
Base
$96,366
Stock
-
Bonus
$18,005
$77,808
$170,800
Interview Experience
6 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Experience
Positive 16%
Neutral 84%
Negative 0%
Interview Process
1
Initial screening (HR/HireVue)
2
Technical rounds
3
Manager/Senior leadership interviews
4
Final round/Superday
Common Questions
Technical knowledge assessment
Behavioral questions
Role-specific scenarios
Leadership and teamwork examples
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