📍 Job Overview

• Job Title: Principal Platform Engineer, Assistant Vice President
• Company: State Street
• Location: Hangzhou, Zhejiang, China
• Job Type: On-site, Full-time
• Category: Senior DevOps Engineer / Infrastructure Role
• Date Posted: 2025-06-16
• Experience Level: 8+ years of experience
• Remote Status: On-site

🚀 Role Summary

• Lead a small agile team to deliver highly effective AI solutions, collaborating with global teams to execute on global projects and improve AI best practices.
• Adopt modern AI tools to design and develop AI solutions, disrupting traditional AI development approaches and improving overall productivity.
• Develop, train, and mentor junior data scientists, ensuring their continuous growth and development, and fostering a high-performance team culture.
• Become a subject matter expert in modern AI tools, foundational AI model design, development, and validation by converting financial data and models to mathematical and computer science level design and implementation.
• Integrate, customize, and train known AI models and algorithms in open-source libraries to solve financial market problems and perform validation and bug fixes.

📝 Enhancement Note: This role requires a strong background in AI solution design and development, as well as excellent team collaboration skills and leadership. The ideal candidate will have rich experience in AI application development and a proven track record of delivering enterprise platforms and/or commercializing AI products.

💻 Primary Responsibilities

• AI Solution Delivery: Lead a small agile team to deliver highly effective AI solutions that meet fast-changing business and client needs. Collaborate with global teams to execute on global projects and keep improving model solutions and AI best practices.
• AI Tool Adoption: Adopt various modern AI tools to design and develop AI solutions, disrupting traditional AI development approaches and improving overall productivity.
• Team Development & Mentoring: Develop, train, and mentor junior data scientists, ensuring their continuous growth and development, and fostering a high-performance team culture.
• AI Model Design & Validation: Become a subject matter expert in modern AI tools, foundational AI model design, development, and validation by converting financial data and models to mathematical and computer science level design and implementation.
• AI Model Integration & Customization: Integrate, customize, and train known AI models and algorithms in open-source libraries to solve financial market problems and perform validation and bug fixes.
• AI Model Rationalization & Scalability: Drive model rationalization, reusability, scalability, and implement modern MLOps and model observability.
• AI Model Specification & Validation: Write model specification about problem statement, assumption, data input, methodology, implementation framework, and test result; work with external model validation groups and implement changes for go-live.
• AI Service Operationalization: Support IT integration, QA/UAT, and deployment of AI microservices, operationalizing and productizing resulting models and AI solutions.
• AI Production Issue Resolution: Support production issues pertinent to models and algorithms, including those used in open-source libraries if any.

🎓 Skills & Qualifications

Education:

• Master’s degree required (preferably in computer science, financial mathematics, and financial engineering), PhD preferred.

Experience:

• 8+ years of hands-on coding experience with foundational AI algorithms and familiarity with deep learning neural networks, such as various supervised and unsupervised models and reinforcement learning.
• 8+ years of modern, object-oriented or functional programming and design experience (Python, Java) and proficiency in AI code generation tools like GitHub Co-pilot/Cursor.

Required Skills:

• Proficient in public cloud development environments and native products such as Azure ML, Azure AI Foundry, Snowflake, Databricks Mosaic, or AWS Bedrock/Sagemaker.
• Familiar with major financial instruments, reference data, market data, investment, and risk management concepts.
• Fluent in English and Mandarin; excellent written and verbal communication skills at all stakeholder levels across multiple countries.
• Result-driven, detail-oriented, and candid attitude.

Preferred Skills:

• Prior data scientist role in a financial institution and model validation experience.
• Prior risk and investment management experience in the asset management industry.
• Structured and unstructured data management tools (Snowflake, Databricks, PostgreSQL, Hadoop, etc.).
• Passed Chartered Financial Analyst (CFA) level II or equivalent.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

• Demonstrate a strong track record of delivering enterprise AI platforms and/or commercializing AI products.
• Showcase AI application development projects that highlight your creativity, problem-solving skills, and self-motivation.
• Include projects that exhibit your ability to deliver mission-critical projects with tight timelines and competing priorities.

Technical Documentation:

• Provide detailed documentation of AI models, including problem statements, assumptions, data inputs, methodologies, implementation frameworks, and test results.
• Include information on AI tool adoption, model rationalization, reusability, scalability, and MLOps implementation.
• Demonstrate your understanding of AI production issues and how you have addressed them in previous projects.

💵 Compensation & Benefits

Salary Range: Not specified. Research suggests that for a Senior DevOps Engineer/Infrastructure role in Hangzhou, China, with 8+ years of experience, the average salary range is approximately ¥600,000 - ¥800,000 per year (before tax).

📝 Enhancement Note: Salary estimates are based on regional market research and industry standards for similar roles. Actual salary may vary depending on the candidate's qualifications and the company's compensation structure.

Benefits:

• Medical Care
• Insurance
• Savings Plans
• Flexible Work Programs
• Development Programs
• Educational Support

Working Hours: Full-time position with standard working hours, typically Monday to Friday, 9:00 AM to 6:00 PM, with flexibility for project deadlines and maintenance windows.

🎯 Team & Company Context

🏢 Company Culture

Industry: State Street is one of the largest custodian banks, asset managers, and asset intelligence companies in the world. They provide investment servicing, data & analytics, investment research & trading, and investment management to institutional clients.

Company Size: Large, with a global presence and a extensive network of offices across multiple countries.

Founded: 1792, with a rich history and established reputation in the financial services industry.

Team Structure:

• The Global Head of Data, Analytics & AI Services (GHDAAIS) organization is responsible for providing AI technology services to the Global Advisors business at State Street.
• The role will function as the AI specialist and solution lead for AI-related services, working closely with State Street affiliates, Global Technology Services (GTS), and other third-party vendors used within the SSGA ecosystem globally.
• The role will operate under a federated operating model to deliver against a target end state AI ecosystem blueprint and adopt GTS AI-related technology, risk, security, and data governance standards.

Development Methodology:

• Agile development methodologies, with a focus on delivering high-quality AI solutions that meet business and client needs.
• Collaboration with global teams to execute on global projects and keep improving model solutions and AI best practices.
• Modern AI tools adoption to disrupt traditional AI development approaches and improve overall productivity.

Company Website: https://www.statestreet.com/

📝 Enhancement Note: State Street's company culture emphasizes collaboration, innovation, and a commitment to delivering high-quality solutions to clients. The company values diversity, inclusion, and social responsibility, providing employees with tools to balance their professional and personal lives, and offering opportunities for growth and development.

📈 Career & Growth Analysis

AI Platform Engineering Career Level: This role is a senior-level position within the AI platform engineering career path. The ideal candidate will have extensive experience in AI solution design and development, as well as strong team collaboration skills and leadership.

Reporting Structure: The role reports directly to the Global Head of Data, Analytics & AI Services (GHDAAIS) and will work closely with State Street affiliates, Global Technology Services (GTS), and other third-party vendors used within the SSGA ecosystem globally.

Technical Impact: The role will have a significant impact on the delivery of AI technology services provided to the Global Advisors business at State Street. The role will be responsible for leading the solution delivery of AI technology services and driving the adoption of modern AI tools and best practices.

Growth Opportunities:

• Technical Growth: The role offers opportunities for growth in technical expertise, as the candidate will be expected to become a subject matter expert in modern AI tools, foundational AI model design, development, and validation.
• Leadership Growth: The role provides opportunities for leadership development, as the candidate will be responsible for leading a small agile team and driving the adoption of modern AI tools and best practices.
• Architecture Decision-Making: The role offers opportunities for involvement in architecture decision-making, as the candidate will be responsible for driving model rationalization, reusability, scalability, and implementing modern MLOps and model observability.

📝 Enhancement Note: This role presents significant growth opportunities for candidates with strong technical skills and a desire to lead and innovate in the AI platform engineering space. The role's focus on modern AI tools adoption, AI solution delivery, and team collaboration provides a strong platform for professional development and career advancement.

🌐 Work Environment

Office Type: State Street's Hangzhou office is a modern, collaborative workspace designed to foster innovation and productivity. The office features state-of-the-art technology, multiple monitors, and testing devices to support web development and AI engineering teams.

Office Location(s): Hangzhou, Zhejiang, China

Workspace Context:

• Collaborative Workspace: The office encourages cross-functional interaction between developers, designers, and stakeholders, fostering a culture of collaboration and knowledge sharing.
• Development Tools: The office provides access to modern AI tools, cloud development environments, and other cutting-edge technologies to support AI platform engineering and development.
• Team Interaction: The office facilitates team interaction and collaboration, with dedicated spaces for team meetings, brainstorming sessions, and social events.

Work Schedule: Full-time position with standard working hours, typically Monday to Friday, 9:00 AM to 6:00 PM, with flexibility for project deadlines and maintenance windows.

📝 Enhancement Note: State Street's Hangzhou office provides a modern, collaborative workspace that supports AI platform engineering and development. The office's focus on cross-functional interaction, knowledge sharing, and team collaboration creates an environment that fosters innovation and productivity.

📄 Application & Technical Interview Process

Interview Process:

• Technical Assessment: A technical assessment or coding challenge focused on AI algorithm design, implementation, and validation. Candidates should be prepared to demonstrate their proficiency in modern AI tools, cloud development environments, and programming languages such as Python or Java.
• AI Solution Presentation: A presentation or case study focused on a candidate's previous AI solution delivery experience. Candidates should be prepared to discuss their approach to AI tool adoption, model rationalization, and MLOps implementation.
• Behavioral & Cultural Fit Assessment: An assessment of the candidate's cultural fit, communication skills, and problem-solving abilities. Candidates should be prepared to discuss their approach to team collaboration, leadership, and driving AI best practices.

Portfolio Review Tips:

• AI Solution Demonstration: Highlight your ability to deliver effective AI solutions that meet business and client needs. Include examples of AI solution delivery, AI tool adoption, and AI model design, development, and validation.
• AI Model Documentation: Include detailed documentation of AI models, including problem statements, assumptions, data inputs, methodologies, implementation frameworks, and test results.
• AI Production Issue Resolution: Demonstrate your ability to support production issues pertinent to models and algorithms, including those used in open-source libraries if any.

Technical Challenge Preparation:

• AI Algorithm Design & Implementation: Brush up on your AI algorithm design and implementation skills, with a focus on modern AI tools, cloud development environments, and programming languages such as Python or Java.
• AI Solution Delivery: Review your previous AI solution delivery experience, focusing on AI tool adoption, model rationalization, and MLOps implementation.
• Communication & Technical Explanation: Prepare to communicate your technical approach and explain your AI solution delivery approach to the interview panel.

ATS Keywords: See the comprehensive list of AI development and server administration-relevant keywords for resume optimization, organized by category: programming languages, AI tools, cloud development environments, databases, tools, methodologies, soft skills, industry terms.

📝 Enhancement Note: The interview process for this role will focus on the candidate's technical skills in AI algorithm design, implementation, and validation, as well as their ability to deliver effective AI solutions that meet business and client needs. The candidate's approach to AI tool adoption, model rationalization, and MLOps implementation will also be assessed during the interview process.

🛠 Technology Stack & AI Infrastructure

AI Tools & Libraries:

• Azure ML
• Azure AI Foundry
• Snowflake
• Databricks Mosaic
• AWS Bedrock/Sagemaker
• GitHub Co-pilot/Cursor

Programming Languages:

• Python
• Java

Cloud Development Environments:

• Azure
• AWS

Databases:

• Snowflake
• PostgreSQL
• Hadoop

📝 Enhancement Note: This role requires proficiency in modern AI tools, cloud development environments, and programming languages such as Python or Java. The ideal candidate will have experience working with AI tools such as Azure ML, Azure AI Foundry, Snowflake, Databricks Mosaic, or AWS Bedrock/Sagemaker, as well as familiarity with GitHub Co-pilot/Cursor for AI code generation.

👥 Team Culture & Values

AI Platform Engineering Values:

• Innovation: State Street values innovation in AI platform engineering, encouraging team members to explore new AI tools, approaches, and best practices to drive productivity and improve AI solution delivery.
• Collaboration: State Street emphasizes collaboration across teams, with a focus on knowledge sharing, technical mentoring, and continuous learning.
• Quality: State Street is committed to delivering high-quality AI solutions that meet business and client needs, with a focus on AI model validation, testing, and bug fixes.
• Customer Focus: State Street prioritizes customer focus, with a commitment to understanding client needs and delivering AI solutions that address their unique challenges and opportunities.

Collaboration Style:

• Cross-Functional Integration: State Street encourages cross-functional integration between AI platform engineering teams, designers, and stakeholders, fostering a culture of collaboration and knowledge sharing.
• Code Review Culture: State Street promotes a code review culture, with a focus on peer programming, technical mentoring, and continuous learning.
• Knowledge Sharing: State Street encourages knowledge sharing, with a focus on technical mentoring, collaboration, and continuous learning.

📝 Enhancement Note: State Street's AI platform engineering culture emphasizes innovation, collaboration, quality, and customer focus. The company's commitment to cross-functional integration, code review culture, and knowledge sharing creates an environment that fosters collaboration, learning, and growth.

⚡ Challenges & Growth Opportunities

AI Platform Engineering Challenges:

• AI Tool Adoption: Disrupt traditional AI development approaches and improve overall productivity by adopting various modern AI tools.
• AI Model Rationalization & Scalability: Drive model rationalization, reusability, scalability, and implement modern MLOps and model observability.
• AI Production Issue Resolution: Support production issues pertinent to models and algorithms, including those used in open-source libraries if any.

Learning & Development Opportunities:

• Technical Skill Development: The role offers opportunities for growth in technical expertise, as the candidate will be expected to become a subject matter expert in modern AI tools, foundational AI model design, development, and validation.
• Leadership Development: The role provides opportunities for leadership development, as the candidate will be responsible for leading a small agile team and driving the adoption of modern AI tools and best practices.
• Architecture Decision-Making: The role offers opportunities for involvement in architecture decision-making, as the candidate will be responsible for driving model rationalization, reusability, scalability, and implementing modern MLOps and model observability.

📝 Enhancement Note: This role presents significant challenges and growth opportunities for candidates with strong technical skills and a desire to lead and innovate in the AI platform engineering space. The role's focus on modern AI tools adoption, AI solution delivery, and team collaboration provides a strong platform for professional development and career advancement.

💡 Interview Preparation

Technical Questions:

• AI Algorithm Design & Implementation: Prepare for questions focused on AI algorithm design, implementation, and validation, with a focus on modern AI tools, cloud development environments, and programming languages such as Python or Java.
• AI Solution Delivery: Prepare for questions focused on AI solution delivery, AI tool adoption, model rationalization, and MLOps implementation.
• Problem-Solving: Prepare for questions focused on problem-solving, with a focus on AI production issue resolution and AI solution delivery.

Company & Culture Questions:

• AI Platform Engineering Culture: Prepare for questions focused on State Street's AI platform engineering culture, with a focus on innovation, collaboration, quality, and customer focus.
• Collaboration Style: Prepare for questions focused on State Street's collaboration style, with a focus on cross-functional integration, code review culture, and knowledge sharing.
• AI Platform Engineering Challenges: Prepare for questions focused on the challenges and growth opportunities presented by the role, with a focus on AI tool adoption, AI model rationalization, and AI production issue resolution.

Portfolio Presentation Strategy:

• AI Solution Demonstration: Highlight your ability to deliver effective AI solutions that meet business and client needs. Include examples of AI solution delivery, AI tool adoption, and AI model design, development, and validation.
• AI Model Documentation: Include detailed documentation of AI models, including problem statements, assumptions, data inputs, methodologies, implementation frameworks, and test results.
• AI Production Issue Resolution: Demonstrate your ability to support production issues pertinent to models and algorithms, including those used in open-source libraries if any.

📝 Enhancement Note: The interview process for this role will focus on the candidate's technical skills in AI algorithm design, implementation, and validation, as well as their ability to deliver effective AI solutions that meet business and client needs. The candidate's approach to AI tool adoption, model rationalization, and MLOps implementation will also be assessed during the interview process.

📌 Application Steps

To apply for this AI Platform Engineer, Assistant Vice President position:

• Submit your application through the application link provided in the job listing.
• Portfolio Customization: Tailor your portfolio to highlight your AI solution delivery experience, AI tool adoption, and AI model design, development, and validation. Include detailed documentation of AI models, including problem statements, assumptions, data inputs, methodologies, implementation frameworks, and test results.
• Resume Optimization: Optimize your resume for AI development and server administration roles, with a focus on project highlighting and technical skills emphasis. Include relevant AI development and server administration keywords to improve search visibility.
• Technical Interview Preparation: Prepare for technical interviews focused on AI algorithm design, implementation, and validation, as well as AI solution delivery, AI tool adoption, model rationalization, and MLOps implementation. Brush up on your problem-solving skills and be ready to discuss your approach to AI production issue resolution and AI solution delivery.
• Company Research: Research State Street's AI platform engineering culture, with a focus on innovation, collaboration, quality, and customer focus. Prepare for questions focused on State Street's collaboration style, with a focus on cross-functional integration, code review culture, and knowledge sharing. Understand the challenges and growth opportunities presented by the role, with a focus on AI tool adoption, AI model rationalization, and AI production issue resolution.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and AI platform engineering industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.