AI Engineer, Assistant Vice President

State Street is a global financial services company serving institutional investors, focusing on risk management and performance. The role is part of a global organization building modern platforms with a startup-like agility alongside enterprise-scale stability, offering a highly collaborative, international working environment.

• Strong programming skills in Python
• Experience building production-grade AI/ML systems
• Experience with microservices and API-based architectures
• Hands-on experience with large language models (LLMs), prompt engineering, RAG pipelines, embeddings, vector search, and retrieval systems
• Experience building agent-based AI workflows
• Experience with AI platforms such as Databricks, Azure AI, and AWS AI services
• Knowledge of MLOps / LLMOps including deployment and monitoring
• Ability to optimize AI systems for latency, scale, and cost
• Understanding of data engineering concepts and distributed systems
• Ability to integrate AI systems with enterprise data platforms and APIs
• Experience working in regulated or enterprise environments
• Ability to translate business needs into practical AI solutions
• Strong collaboration and communication skills
• Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or other technical field; Master's degree strongly preferred
• Minimum 8-10 years of relevant experience including 3+ years in AI/ML/Generative AI

Nice to have:

• Experience in financial services or capital markets
• Familiarity with Databricks or Snowflake
• Experience building AI copilots and document intelligence solutions
• Exposure to AI governance or model risk frameworks

AI Engineering & Development:

• Design, build, and deploy production AI and ML solutions
• Develop large language model-based applications including prompt engineering and inference workflows
• Build RAG pipelines with structured and unstructured enterprise data
• Implement embeddings, semantic search, and vector-based retrieval
• Develop agent-based and multi-step AI workflows

Production Delivery & Operations:

• Build and maintain AI services and APIs for enterprise use
• Implement MLOps / LLMOps practices including deployment, versioning, monitoring, evaluation, logging, and rollback
• Optimize systems for performance, scalability, and cost efficiency
• Integrate AI solutions with Databricks, Snowflake, and cloud platforms (Azure, AWS)

Data & Integration:

• Ensure data readiness for AI use cases (quality, access, transformation)
• Integrate AI solutions with enterprise data platforms and APIs
• Partner with data teams to support AI-driven pipelines and workflows

Governance & Risk:

• Implement controls for data privacy, security, and model reliability
• Apply validation, explainability, and hallucination mitigation techniques
• Align AI implementations with enterprise standards for compliance and auditability

Use Case Delivery:

• Translate business problems into deployable AI solutions
• Deliver use cases such as intelligent document processing, AI copilots for operations and analytics, and data-driven insights for markets and corporate functions

The role requires a minimum of three days per week working from the office. Candidates must be able to work in a hybrid model balancing remote and office presence. Equal opportunity employer statement applies.