Artificial Intelligence & Machine Learning, AVP
State Street23 hours ago
Hangzhou, ChinaStaff+
Responsibilities
- Define and own the end-to-end target-state architecture for the Agentic AI platform.
- Lead the design and implementation of production-grade agentic AI solutions for investment performance, investment research, data operations, and related workflows.
- Establish architectural principles, engineering standards, reusable patterns, guardrails, and adoption practices.
- Define standards for an Apache Iceberg-based lakehouse, including table design, partitioning, schema evolution, metadata, performance, and lifecycle management.
- Design enterprise knowledge capabilities using retrieval-augmented generation, vector search, knowledge graphs, ontologies, metadata, and semantic retrieval.
- Review platform, data, and solution designs for architectural, performance, security, and enterprise-standard alignment.
- Partner with platform engineering, enterprise architecture, governance, risk, and security teams on infrastructure, access management, observability, compliance, Responsible AI, AgentOps, and LLMOps.
- Publish reference architectures, design guidelines, engineering patterns, and architectural decision records.
- Identify technical risks, technical debt, and improvement opportunities and guide platform evolution.
- Mentor senior engineers and influence technical direction across multiple engineering and application teams.
Requirements
- Bachelor's or master's degree in computer science, artificial intelligence, machine learning, software engineering, data engineering, or a related discipline.
- 10+ years of experience in software engineering, platform engineering, data engineering, solution architecture, or related technology roles.
- Proven experience owning or leading enterprise-scale Agentic AI or Generative AI architecture and delivery.
- Deep knowledge of agent orchestration, planning, memory, tool calling, evaluation, guardrails, multi-agent systems, and human-in-the-loop design.
- Hands-on experience with agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, Google ADK, or comparable technologies.
- Strong experience with Python, APIs, microservices, distributed systems, event-driven design, and cloud-native engineering.
- Experience designing retrieval-augmented generation and enterprise knowledge solutions using vector databases, knowledge graphs, ontologies, metadata, and hybrid retrieval.
- Experience with distributed data platforms such as Apache Spark, Apache Iceberg, Databricks, Kafka, Delta Lake, Snowflake, or comparable platforms.
- Experience architecting platforms and AI solutions on AWS, Google Cloud Platform, and/or Microsoft Azure.
- Understanding of Kubernetes, containers, infrastructure as code, CI/CD, observability, security architecture, data governance, and metadata management.
- Ability to operate as an AI-augmented architect using Generative AI tools while maintaining architectural judgment and quality standards.
- Knowledge of Responsible AI, AI governance, model risk, AgentOps, LLMOps, and production support practices.
- Ability to lead complex technical initiatives across organizational and geographic boundaries.
- Experience in financial services, investment management, or another large-scale regulated enterprise is preferred.
- Relevant cloud, architecture, data, or AI certifications are preferred but not required.
Benefits
- Inclusive development opportunities, flexible work-life support, paid volunteer days, and employee networks are offered.
- The employer provides equal employment opportunity and considers qualified applicants without regard to legally protected characteristics.
Tech Stack
Categories
About State Street
State Street is a global custodian bank and asset manager serving institutional investors with investment servicing, fund accounting, trading/FX, data, and index/active strategies. Its products include State Street Global Advisors’ funds and ETFs, the Charles River Investment Management Solution, and the front-to-back State Street Alpha platform. Founded in 1792 and headquartered in Boston, the company is publicly traded on the NYSE (ticker: STT) and operates across major markets worldwide.