Infrastructure Product Development AI Engineer

Northern Trust

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Chicago, IL
Salary
$80,800–$133,400 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k
This role $107k
$60k $276k
below market most similar roles pay here above market

This role pays less than 99% of similar roles. Most pay $165,500–$242,312 — the blue band above. At the midpoint, this role pays about $107k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Northern Trust

Northern Trust is a leading provider of wealth management, asset servicing, asset management, and banking services to corporations, institutions, and high-net-worth individuals. Industry: Financial Services & Asset Management

Northern Trust currently has 109 open roles on FindRole.

Listed pay typically runs $114,500–$194,700 across 75 roles with salary data.

Most-posted roles

View all roles at Northern Trust

At a glance

TL;DR · Infrastructure Product Development AI Engineer

The SQM Infrastructure Product Development AI Engineer joins the team to design, build, and deploy enterprise-grade Generative AI solutions. This role involves managing the full product lifecycle, from architecture and prototyping to API development, deployment, and production support. The engineer will build multi-step agentic AI workflows, Retrieval-Augmented Generation solutions, and scalable backend services. Key technologies include Python, FastAPI, LangChain, LangGraph, and LangSmith. The candidate will utilize Azure OpenAI, Azure Kubernetes Service, PostgreSQL, and pgvector for vector storage and semantic retrieval. Core responsibilities include designing prompt patterns, implementing observability mechanisms, and ensuring production-ready practices like exception handling and security. The work focuses on converting business requirements into scalable AI product capabilities, specifically addressing LLM hallucination, grounding, and context management within an enterprise environment.

What you'll do

  • Design and develop enterprise Generative AI and agentic AI applications using LangChain, LangGraph, and LangSmith.
  • Build multi-step 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.
  • Build scalable backend services and REST APIs using Python and FastAPI.
  • Develop evaluation and observability mechanisms to measure AI response quality, latency, and reliability.
  • Containerize and deploy AI services to Azure Kubernetes Service (AKS) using Azure cloud-native services.
  • Convert business requirements into scalable AI product capabilities and production-ready features.
  • Troubleshoot production LLM/RAG applications and resolve major incidents with infrastructure and operations teams.

What we're looking for

  • Design and develop enterprise Generative AI and agentic AI applications using LangChain, LangGraph, and LangSmith.
  • Develop Retrieval-Augmented Generation (RAG) solutions using PostgreSQL and pgvector for vector storage and semantic retrieval.
  • Build scalable backend services and REST APIs using Python and FastAPI.
  • Containerize and deploy AI services to Azure Kubernetes Service (AKS) using cloud-native engineering practices.
  • Integrate applications with Azure OpenAI and other LLM-based services.
  • Translate business requirements into technical product capabilities and own features through design, development, and production stabilization.
  • Experience building internal developer, infrastructure, automation, operations, or knowledge-management AI products is a plus (preferred).
  • Work Authorization.

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