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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Orchestration Engineer - **Company:** State Street - **Location:** United States - **Experience:** Experienced - **Salary:** $90,000.0 - $157,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Cloud Engineering, Information Systems, Information Engineering, Data Governance, Database Development, Distributed Data Store, Python (Programming Language), Machine Learning, Search Technologies, Software Engineering, SQL Databases, Management of Software Versions, Enterprise Data Management, Enterprise Software Applications, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Apache Spark, Generative AI, Data Lakes, AI Platforms, Information Technology, Apache Kafka, Machine Learning Operations, Virtual Agents, Data Pipelines, Databricks - **Published:** September 12, 2026 - **Apply:** https://www.dice.com/job-detail/27f00f3b-293e-4e13-904d-225d62a69ae9 ## About the Role * 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. ## Description 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., * 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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