This role pays less than
59%
of similar roles. Most pay
$151,000–$213,200
— the shaded band above.
At the midpoint, this role pays about
$169k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About State Street
State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody
State Street currently has
176 open roles
on FindRole.
Listed pay typically runs
$120,000–$202,500
across 172 roles with salary data.
The Platform Engineering Lead, VP joins the Global Technology Services team to lead the design, development, and deployment of solutions for document processing, intelligent agents, and automation frameworks. This role involves building reusable components, evaluation pipelines, and scalable data architecture patterns for fund accounting, custody, and reference data domains. The successful candidate will manage complex investment data concepts such as NAV, positions, and transactions while ensuring robust data lineage and quality controls in a regulated environment. Technical requirements include proficiency in Python, PySpark, Apache Spark, and Databricks, along with experience using FastAPI, PyTorch, TensorFlow, Pandas, LangChain, and tools like Fiddler and Postman. The role also requires expertise in building generative AI models via OpenAI or Hugging Face while ensuring responsible practices regarding security, compliance, and explainability across enterprise data platforms.
Ensure all deployments adhere to responsible AI practices, including security, compliance, and explainability.
What we're looking for
Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related field.
12+ years in IT delivery including 3+ years of hands-on experience in AI/ML and data engineering.
Expertise in Python, Apache Spark, PySpark, and Databricks for large-scale data processing and AI model development.
Experience designing, deploying, and evaluating machine learning and generative AI models using platforms like OpenAI, Hugging Face, Azure OpenAI, and LangChain.
Proficiency in software engineering principles including OOPS, design patterns, data structures, and algorithms.
Deep understanding of fund accounting, custody, and reference data domains to build scalable data architecture.
Experience designing data lineage, quality, reconciliation, and governance controls for regulated financial services platforms.