Data Engineering - AI Platform Engineer

Design, build, and run core services and reusable components for the open-architecture data platform, enabling scalable ingestion, metadata-driven processing, governance, and reliable multi-engine data consumption. Partner with Platform Engineering and Data Engineering teams to provide secure, observable, production-grade capabilities that support Core Reference, IBOR, and Stamford data initiatives. Meanwhile, build Agentic AI solutions/platform to automate data operations related to investment performance, investment research, sales, client coverage, product, and related daily operations.

Key Responsibilities

Build agentic AI solutions to automate data operations related to investment performance, investment research, and related daily operations.

Implement platform security controls including role-based access control, authentication, and integration with enterprise entitlements

Build and maintain platform observability (logging, metrics, traces), alerting, and operational dashboards in support of SLAs

Collaborate with architects to define scalable, extensible designs and ensure adherence to open standards

Drive engineering excellence through code reviews, automated testing, CI/CD, and production readiness practices

Ensure platform services meet enterprise security and compliance requirements (SCC, governance)

Participate in on-call / major incident management and troubleshoot production issues to maintain platform stability

Qualifications

Strong programming skills in Python and Java ; Vibe coding is a must.

Proficient in h arness Engineering including but not limited skills, MCP tools, workflow orchestration, agent memory, RAG and knowledge graph etc.

Hands-on experience with Snowflake and Databricks as data platforms

Strong understanding of SQL optimization, execution, and large-scale analytics Deep understanding of distributed computing and hyperscale

Experience building production-grade services in cloud environments; AWS ,GCP and/or Azure is preferred

Familiarity with streaming pipelines and Kafka is preferred

Understanding of data modeling and data product design

Experience with CI/CD, containers, and Kubernetes

Financial/data platform background preferred but not required

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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