AI Systems Architect: Strategy, Scale & MLOps

Highmark Health; Honolulu (HI); On-site; USD 118,000 - 197,000; Full time

Job summary

enGen is seeking an AI Architect to define the end-to-end architecture for AI solutions and to lead the integration of AI across the enterprise. You will design scalable, secure data pipelines, model storage, inference engines, and front-end integration while selecting the optimal tech stack for long-term AI initiatives.

The role requires 5+ years in software or data science and 3+ years in architecture, with strong cross-functional leadership and experience in enterprise integration and

Qualifications

• Requires 5+ years in software engineering or data science.
• At least 3 years in an architectural role.
• Experience with enterprise integration and migrating legacy systems to AI-augmented workflows.
• Ability to mentor engineers and present to C-suite.

Responsibilities

• Define end-to-end AI architecture including data pipelines, model storage, inference engines, and front-end integration.
• Design scalable, secure systems and best practices for MLOps and deployment strategies.
• Lead cross-functional teams and align AI roadmap with infrastructure capabilities.
• Establish data privacy, governance, and AI safety guardrails.
• Evaluate tech stack (LLMs, databases, orchestration) and drive architecture decisions.

Skills

Cross-functional leadership

Architectural expertise

Distributed systems

Microservices architecture

API design

AWS SageMaker

Azure ML

GCP Vertex AI

PyTorch

TensorFlow

RAG

Generative AI

Education

Bachelor’s Degree in Information Technology or closely related field

Master's Degree

Tools

Terraform

Ansible

Kubeflow

MLflow

BentoML

PyTorch

TensorFlow

SageMaker

Azure ML

Vertex AI

Job description

enGen is seeking an AI Architect to define the end-to-end architecture for AI solutions and to lead the integration of AI across the enterprise. You will design scalable, secure data pipelines, model storage, inference engines, and front-end integration while selecting the optimal tech stack for long-term AI initiatives.

The role requires 5+ years in software or data science and 3+ years in architecture, with strong cross-functional leadership and experience in enterprise integration and