AI Orchestration Engineer, Vice President

State Street; Kilkenny; On-site; EUR 90,000 - 140,000; Full time

Job summary

State Street seeks an AI Orchestration Engineer to design, engineer, and operationalize scalable AI orchestration frameworks across cybersecurity data platforms, LLMs, and enterprise knowledge sources. You will build multi‑agent workflows, retrieval‑augmented generation systems, and monitoring capabilities to ensure secure, auditable AI in a regulated financial services environment.

The role emphasizes hands-on data engineering and AI engineering, with focus on MLOps/LLMOps, governance, and

Qualifications

• Bachelor's degree or equivalent practical experience in a relevant field.
• 3–5 years of experience in Data Engineering, AI Engineering, ML Engineering, Software Engineering, or related disciplines.
• Strong experience developing large-scale data pipelines and distributed data-processing solutions.
• Experience with Python, SQL, APIs, workflow automation, and cloud-native architectures.
• Strong communication and stakeholder collaboration skills.

Responsibilities

• Design and engineer AI orchestration frameworks that coordinate multiple models, agents, tools, APIs, and enterprise applications.
• Develop agent-to-agent and human-in-the-loop workflows that automate complex operational and analytical processes.
• Build reusable orchestration patterns that enable rapid deployment of AI-enabled business capabilities.
• Design and develop scalable data pipelines supporting AI, analytics, and agentic workflows.
• Build enterprise data products optimized for AI consumption.
• Design and implement enterprise RAG architectures.
• Develop reusable AI platform components supporting multiple use cases and business domains.
• Implement MLOps and LLMOps deployment, monitoring, versioning, and governance capabilities.
• Implement Responsible AI guardrails, governance controls, and model risk management processes.
• Build AI observability, evaluation, telemetry, and performance measurement solutions.

Skills

AI Orchestration

Agentic AI

Enterprise AI Platforms

Data Engineering

RAG Architecture

Vector Databases

Prompt Engineering

MLOps / LLMOps

AI Observability

Responsible AI

Model Governance

Human-in-the-Loop AI

Python / SQL development

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Artificial Intelligence, or equivalent practical experience

Tools

LangGraph

Semantic Kernel

CrewAI

AutoGen

LangChain

Databricks

Snowflake

Spark

Kafka

Delta Lake

Airflow

Job description

Who We Are Looking For

The State Street Global Cybersecurity (GCS) organization is seeking an AI Orchestration Engineer to help build the next generation of enterprise AI capabilities across Cybersecurity functions. As part of the GCS team, you will operate at the intersection of Artificial Intelligence, Agentic Systems, Data Engineering, and Enterprise Governance. This role is responsible for designing, engineering, and operationalizing scalable AI orchestration frameworks that transform enterprise data into intelligent, auditable, and secure business outcomes. This role requires strong capabilities in both AI Engineering and Data Engineering. You will design data products, orchestrate multi‑agent workflows, develop Retrieval‑Augmented Generation (RAG) systems, integrate enterprise knowledge sources, and establish the governance and observability capabilities required to operate AI safely within a highly regulated financial services environment.

Why This Role Is Important To Us

State Street is accelerating the adoption of AI‑enabled capabilities to improve operational efficiency, enhance cybersecurity resilience, strengthen risk management, and deliver intelligent experiences across the enterprise. As an AI Orchestration Engineer, you will help establish the AI execution layer that enables secure collaboration between enterprise data platforms, large language models, internal knowledge repositories, agentic workflows, governance controls, and human decision makers.

What You Will Be Responsible For

• Design and engineer AI orchestration frameworks that coordinate multiple models, agents, tools, APIs, and enterprise applications.
• Develop agent‑to‑agent and human‑in‑the‑loop workflows that automate complex operational and analytical processes.
• Build reusable orchestration patterns that enable rapid deployment of AI‑enabled business capabilities.
• Design and develop scalable data pipelines supporting AI, analytics, and agentic workflows.
• Build enterprise data products optimized for AI consumption.
• Design and implement enterprise RAG architectures.
• Develop reusable AI platform components supporting multiple use cases and business domains.
• Implement MLOps and LLMOps deployment, monitoring, versioning, and governance capabilities.
• Implement Responsible AI guardrails, governance controls, and model risk management processes.
• Build AI observability, evaluation, telemetry, and performance measurement solutions.

Education & Qualifications

Minimum Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Artificial Intelligence, or equivalent practical experience.
• 3–5 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, Software Engineering, or related disciplines.
• Strong experience developing large‑scale data pipelines and distributed data‑processing solutions.
• Experience with Python, SQL, APIs, workflow automation, and cloud‑native architectures.
• Strong communication and stakeholder collaboration skills.

Preferred Qualifications

• LangGraph, Semantic Kernel, CrewAI, AutoGen, LangChain, or similar frameworks.
• Databricks, Snowflake, Spark, Kafka, Delta Lake, Iceberg, and Airflow.
• Experience with vector databases, semantic search, and enterprise RAG platforms.
• Experience implementing MLOps, LLMOps, AI observability, and evaluation frameworks.
• Knowledge of Responsible AI, data governance, and model risk management.

Success Measures

• Accelerate delivery of AI‑enabled business capabilities through reusable orchestration frameworks.
• Increase adoption of governed enterprise AI services.
• Improve enterprise data accessibility for AI use cases.
• Enhance reliability, observability, and auditability of AI systems.
• Reduce operational complexity through agentic automation and intelligent workflows.

Core Competencies

• AI Orchestration
• Agentic AI
• Enterprise AI Platforms
• Data Engineering
• RAG Architecture
• Vector Databases
• Prompt Engineering
• MLOps / LLMOps
• AI Observability
• Responsible AI
• Model Governance
• Human‑in‑the‑Loop AI Systems
• Python / SQL development

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.

Discover more information on jobs at StateStreet.com/careers

Read our CEO Statement

Job ID: R-794424