Lead AI & Cloud-Native Architect (Distributed Systems)

Morningstar; Illinois; Hybrid; USD 118,000 - 123,000; Full time

Benefits offered by this job

401(k) match

Stock ownership potential

Comprehensive health benefits

Job summary

Morningstar is seeking an Architect to lead the development of scalable AI and cloud-native Agentic solutions, leveraging OpenAI, Azure, and AWS to enhance financial data automation. You will design, code, debug, and upgrade high-performance software while guiding multiple teams and ensuring alignment with business goals.

You will drive architectural decision-making, enforce coding standards, and advance best practices for reliability, security, and reusability across platforms.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a technology-related field or foreign equivalent with 8+ years of software engineering experience in lead roles.
• Master's degree with 6+ years of software engineering experience accepted as alternative.

Responsibilities

• Architect and lead development of scalable AI and cloud-native solutions across AWS, Azure, and OpenAI integrations.
• Provide technical leadership across multiple engineering teams and guide architectural decision-making.
• Lead DevOps efforts with Docker, Kubernetes, and AWS Fargate; implement CI/CD pipelines and automated deployments.

Skills

OpenAI

Python

Java

AWS

Azure

Docker

Kubernetes

CI/CD

DevOps

ML/AI

Education

Bachelor's degree in Computer Science/Engineering

Master's degree in Computer Science/Engineering

Tools

AWS Fargate

SonarQube

Job description

Morningstar is seeking an Architect to lead the development of scalable AI and cloud-native Agentic solutions, leveraging OpenAI, Azure, and AWS to enhance financial data automation. You will design, code, debug, and upgrade high-performance software while guiding multiple teams and ensuring alignment with business goals.

You will drive architectural decision-making, enforce coding standards, and advance best practices for reliability, security, and reusability across platforms.