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AI Orchestration Engineer

  • Source: Workday
  • 1037 State Street Financl Srvc, Inc
  • $120,000 to $202,500 /yr
  • On-site
  • Quincy
  • Full-Time
  • Mid level

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

Salary Range:

$120,000 - $202,500 Annual

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

*Employees are eligible to…

Skills

  • guardrails
  • Python
  • LangGraph
  • crewai
  • LangChain
  • azure-databricks
  • databricks
  • Snowflake
  • Spark
  • Kafka
  • delta-lake
  • Airflow
  • apache-airflow
  • phenom-people
  • workday
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