Principal, AI Engineer

## Principal, AI Engineer Apply locations:
Chicago, ILtime type:
Full time posted on:
Posted 2 Days Agojob requisition :
R157016
** About Northern Trust
** As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world’s most successful individuals, families, corporations and institutions.  Since 1889, we have aligned our efforts with our three guiding Principles That Endure:
Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide.  With more than 135 years of financial experience and over 24,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service.

** Job Description Summary
** As a key member of our AI Engineering team who builds, ships, and owns production-grade generative AI systems, the lead the design and implementation of secure, scalable, and compliant AI platform powered by LLM’s-powered on
** Azure AI Foundry**, working across multiple model providers (
** Claude / Anthropic**,
** GPT / OpenAI**, and others), applying modern
** AI design patterns** (RAG, agents, tool use, orchestration) to solve real business problems in a highly regulated financial environment.
** Job Description
** 1.
Lead development of a portfolio of client-facing AI capabilities and integration methods, embedding them into client front ends and interactive dashboards to ensure these capabilities are well aligned and meet required validation and responsible AI standards.
2.
Develop and oversee business unit wise approach to integrate structured and unstructured data into NT’s enterprise AI framework in collaboration with the AI architecture, AI engineering, and data platform engineering teams.
3.
Develop and lead the practice of data pipeline engineering, rationalizing custom data integrations over time to establish common methods and approaches.
4.
Architect and implement data pipelines that integrate structured and unstructured data from internal banking systems, external feeds, and cloud platforms for AI/ML use cases.
5.
Drive our semantic architecture and engineering approach for Northern Trust intelligence to advance enterprise context engineering and architecture disciplines.
6.
Collaborate with the AI consulting team, business units, data scientists, model risk teams, and other stakeholders to understand data requirements for AI models supporting key use cases such as portfolio management, quants & research, reconciliations, and customer intelligence; drive engineering specifications and delivery for these capabilities.
7.
Ensure sound practices are executed to deliver and maintain metadata management, data lineage, and audit trails for AI data assets as development and data teams expand AI data access.
8.
Provide leadership to multiple Technical Delivery teams to prioritize and refine critical data deliverables based on business use cases and high-value data assessments.
9.
Work closely on vendor negotiations and guide data solutions with procurement and transformation teams to enable scalable consumption with favorable and appropriate terms and capabilities, including understanding support or vendor SLA requirements.
10.
Provide guidance for regulatory compliance processes, audits, and internal reviews.
11.
Act as End-to-End Data Integration Product Management Vision and Roadmap leader in support of AI transformation programs.
12.
Support real-time and batch data ingestion from asset management vendor platforms i.e. Aladdin, Eagle, iCapital, and third-party APIs.
13.
Optimize data workflows for performance, reliability, and cost-efficiency across hybrid cloud environments.
14.
Partner with cybersecurity and compliance teams to ensure data privacy, encryption, and access controls are enforced.
15.
Contribute to the development of enterprise-wide AI architecture standards and governance frameworks, ensuring secure and efficient data consumption.
16.
Provide indirect leadership across lateral teams of data…