AI Systems Architect — Enterprise-Scale & MLOps Leader

Highmark Health; Helena (MT); On-site; USD 118,000 - 197,000; Full time

Benefits offered by this job

Health insurance

Remote-friendly options

Job summary

enGen seeks an AI Architect to define the end-to-end architecture of AI solutions, including data pipelines, model storage, inference, and front-end integration. You will select the tech stack (LLMs, vector databases, orchestration) and establish MLOps, security, and governance for scalable, low-latency systems.

You will lead cross-functional collaboration with Data Science, DevOps, and Product teams, ensuring alignment with business goals and infrastructure capabilities.

Qualifications

• 5+ years in software engineering or data science.
• At least 3 years in an architectural role.
• Experience in enterprise integration migrating legacy systems to AI-augmented workflows.
• Thought leadership and mentoring of engineers.

Responsibilities

• Lead strategic consultation to define business processes and enabling technologies.
• Specify and design complex systems and ensure cross-system integration.
• Translate requirements into detailed architectural designs and select tech stack.
• Define non-functional requirements and drive improvement programs.
• Resolve architecture issues and mentor peers and teams.
• Communicate clearly with executives and stakeholders.

Skills

IMS

DB2

Oracle

Teradata

Data Warehousing

COBOL

Visual Basic

C

C++

SAS

Java/JavaScript

PEGA

CSS3

Mobile

JSON

Cognos

Hadoop

SQL

J2EE

HTML5/XML

Project Management Tools: Waterfall/Ag

Education

Bachelor’s Degree in Information Technology or closely related field

Master's Degree

Tools

Terraform

Ansible

SageMaker

Azure ML

Vertex AI

Kubeflow

MLflow

BentoML

PyTorch

TensorFlow

Job description

enGen seeks an AI Architect to define the end-to-end architecture of AI solutions, including data pipelines, model storage, inference, and front-end integration. You will select the tech stack (LLMs, vector databases, orchestration) and establish MLOps, security, and governance for scalable, low-latency systems.

You will lead cross-functional collaboration with Data Science, DevOps, and Product teams, ensuring alignment with business goals and infrastructure capabilities.