SQM Infrastructure Product Development AI Engineer

The Northern Trust Company; Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Job summary

The Northern Trust Company is seeking an AI Engineer to design, build and deploy enterprise-grade Generative AI solutions. You will work across the full product lifecycle from architecture to production support, focusing on scalability, reliability, security and user experience.

Responsibilities include designing AI applications with LangChain, building multi-step workflows, integrating with Azure OpenAI, and deploying services via AKS.

Qualifications

• Experience taking AI capabilities from concept to production products.
• Translate business requirements into technical AI product capabilities.
• Design reusable AI architectures balancing quality, latency, cost, and security.
• Develop enterprise APIs and integration patterns.

Responsibilities

• Design and develop enterprise Generative AI and agentic AI apps using LangChain/LangSmith/LangGraph.
• Create multi-step AI workflows with reasoning, tool integration and human-in-the-loop patterns.
• Build and deploy REST APIs with Python/FastAPI and containerize on AKS.

Skills

Generative AI

LLMs

Azure OpenAI

RAG

Prompt Engineering

Agentic AI / AI Agents

LLM evaluation

AI Frameworks

LangChain

LangGraph

LangSmith

Application Engineering

Python

FastAPI

REST APIs

Async/API development

Microservices

PostgreSQL

pgvector

Vector embeddings

Semantic/vector search

RAG retrieval

Cloud & Deployment

Microsoft Azure

AKS

Containers/Docker

CI/CD

Tools

LangChain

LangSmith

LangGraph

Azure OpenAI

PostgreSQL

pgvector

AKS

Python

FastAPI

REST APIs

Docker

Cloud-native

Job description

About Northern TrustAs 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: AI Engineer - Generative AI & Product Engineering

We are seeking a hands-on AI Engineer with strong product development experience to design, build, and deploy enterprise-grade Generative AI solutions. The ideal candidate combines expertise in LLMs, RAG, agentic AI, Python, Azure, and cloud-native engineering with a product mindset focused on scalability, reliability, security, and user experience. The engineer will work across the full product lifecycle, from architecture and prototyping through API development, deployment, evaluation, monitoring, and production support.

Key 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 (RAG) solutions using PostgreSQL and pgvector for vector storage and semantic retrieval.
• Integrate applications with Azure OpenAI and other LLM-based services.
• Design effective prompts and reusable prompt patterns using advanced prompt engineering techniques.
• Build scalable backend services and REST APIs using Python and FastAPI .
• Develop evaluation and observability mechanisms for measuring AI response quality, latency, reliability, and retrieval effectiveness.
• Use LangSmith for tracing, evaluation, debugging, and observability of LLM/agent workflows.
• Containerize and deploy AI services to Azure Kubernetes Service (AKS) .
• Design solutions using appropriate 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 closely with product owners, architects, and engineering teams to convert business requirements into scalable AI product capabilities.
• Participate in architecture/design reviews, code reviews, testing, deployment, troubleshooting, and ongoing product enhancement.
• Evaluate emerging LLM, retrieval, agentic AI, and AI engineering techniques and apply them where 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.

Required Technical Skills

• Generative AI
• Large Language Models (LLMs)
• Azure OpenAI
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Agentic AI / AI Agents
• LLM evaluation and observability
• AI Frameworks
• LangChain
• LangGraph
• LangSmith
• Application Engineering
• Python
• FastAPI
• REST APIs
• Async/API development
• Microservices architecture
• Data & Vector Search
• PostgreSQL
• pgvector
• Vector embeddings
• Semantic/vector search
• RAG retrieval and indexing patterns
• Cloud & Deployment
• Microsoft Azure
• Azure Kubernetes Service (AKS)
• Containers/Docker
• Cloud-native application development
• CI/CD and production deployment practices

Product Development Experience

The candidate should demonstrate experience taking AI capabilities beyond proof-of-concept into production products , including:

• Translating business requirements into technical product capabilities
• Designing reusable and maintainable AI architectures
• Balancing model quality, latency, cost, security, and scalability
• Designing APIs and integration patterns for enterprise applications
• Establishing AI evaluation and quality measures
• Troubleshooting production LLM/RAG applications
• Collaborating across engineering, architecture, product, QA, DevOps, and business teams
• Owning features through design, development, testing, deployment, and production stabilization

Preferred Qualifications

• Strong hands-on experience developing enterprise GenAI/RAG products
• Experience building LangGraph-based agentic workflows
• Hands-on experience with LangSmith tracing and evaluation
• Experience deploying Python/FastAPI applications on AKS
• Experience with PostgreSQL/pgvector at production scale
• Understanding of LLM hallucination, grounding, context management, guardrails, and evaluation
• Familiarity with Azure identity, secrets management, monitoring, and enterprise security patterns
• Experience building