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Northern Trust

Global wealth management and asset servicing

AI Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeChicago, IL, USA$80.8k - $133.4kIn-person

About the Job

Requirements

  • Demonstrated experience taking AI capabilities beyond proof of concept into production products.
  • Ability to translate business requirements into technical product capabilities.
  • Ability to design reusable and maintainable AI architectures.
  • Ability to balance model quality, latency, cost, security, and scalability.
  • Experience designing APIs and integration patterns for enterprise applications.
  • Ability to establish AI evaluation and quality measures.
  • Experience troubleshooting production large language model and Retrieval-Augmented Generation applications.
  • Ability to collaborate across engineering, architecture, product, quality assurance, DevOps, and business teams.
  • Experience owning features through design, development, testing, deployment, and production stabilization.
  • Required technical skills include large language models, Azure OpenAI, Retrieval-Augmented Generation, prompt engineering, agentic AI and AI agents, and large language model evaluation and observability.
  • Required frameworks include LangChain, LangGraph, and LangSmith.
  • Required application engineering skills include Python, FastAPI, REST APIs, asynchronous/API development, and microservices architecture.
  • Required data and vector search skills include PostgreSQL, pgvector, vector embeddings, semantic/vector search, and Retrieval-Augmented Generation retrieval and indexing patterns.
  • Required cloud and deployment skills include Microsoft Azure, Azure Kubernetes Service, containers/Docker, cloud-native application development, CI/CD, and production deployment practices.

Responsibilities

  • Design and develop enterprise Generative AI and agentic AI applications using LangChain, LangSmith, and LangGraph.
  • Build multi-step and stateful AI workflows involving reasoning, tool integration, retrieval, and human-in-the-loop patterns.
  • Develop Retrieval-Augmented Generation solutions using PostgreSQL and pgvector for vector storage and semantic retrieval.
  • Integrate applications with Azure OpenAI and other large language model-based services.
  • Design effective prompts and reusable prompt patterns using prompt engineering techniques.
  • Build scalable backend services and REST APIs using Python and FastAPI.
  • Develop evaluation and observability mechanisms to measure AI response quality, latency, reliability, and retrieval effectiveness.
  • Use LangSmith for tracing, evaluation, debugging, and observability of large language model and agent workflows.
  • Containerize and deploy AI services to Azure Kubernetes Service.
  • Design solutions using Azure services for identity, security, networking, storage, monitoring, and application integration.
  • Implement production-ready practices including exception handling, logging, retries, API security, configuration management, and observability.
  • Work with product owners, architects, and engineering teams to translate business requirements into scalable AI product capabilities.
  • Participate in architecture and design reviews, code reviews, testing, deployment, troubleshooting, and ongoing product enhancement.
  • Evaluate emerging large language model, retrieval, agentic AI, and AI engineering techniques and apply them when they provide measurable product value.
  • Partner with application, infrastructure, cloud, database, and operations teams during major incidents and production issues to identify dependencies and resolve problems.

Desired Qualifications

  • Strong hands-on experience developing enterprise Generative AI and Retrieval-Augmented Generation products.
  • Experience building LangGraph-based agentic workflows.
  • Hands-on experience with LangSmith tracing and evaluation.
  • Experience deploying Python/FastAPI applications on Azure Kubernetes Service.
  • Experience with PostgreSQL and pgvector at production scale.
  • Understanding of large language model hallucination, grounding, context management, guardrails, and evaluation.
  • Familiarity with Azure identity, secrets management, monitoring, and enterprise security patterns.
  • Experience building internal developer, infrastructure, automation, operations, or knowledge-management AI products.

About the Company

Northern Trust

Global wealth management and asset servicing

Preparing company summary.

Company size
10,001+
Company stage
IPO
Headquarters
Chicago, IL
Founded
1889

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