AI/ML Architect for SaaS Data Platforms

ASG

United States

Remote

USD 200,000 - 250,000

Full time

2 days ago
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Job summary

ASG is seeking an AI/ML Engineer to lead and build AI/ML systems across its portfolio of SaaS companies. You will develop data platforms, internal LLM apps, data pipelines and scalable infrastructure, delivering practical business value from data.

You will work with operating companies to deploy models, design pipelines, and drive AI adoption, while sharing best practices and enabling teams across multiple companies.

Qualifications

  • Experience deploying machine learning, data engineering, and applied AI solutions at scale.
  • Familiarity with LLM-based applications, model APIs, retrieval workflows, evaluation patterns and production deployment.

Responsibilities

  • Lead high-impact AI/ML and data engineering projects across ASG portfolio companies.
  • Build hands-on across AI/ML systems, including data pipelines, model integrations, internal LLM applications, APIs, and supporting infrastructure.
  • Develop LLM-powered tools and workflows that enhance business operations, internal productivity, and product capabilities.
  • Partner with portfolio companies to identify opportunities to commercialize data through new products, features, and analytics offerings.
  • Serve as a technical leader and trusted advisor to engineering and data teams across the portfolio.

Skills

ML deployment
Data engineering
Applied AI
Cross-company collaboration
Architecting AI systems

Tools

Bedrock
Sagemaker
Vertex AI
Glue
Airflow
Spark
Hadoop
Kafka
BigQuery
Databricks

Job description

ASG is seeking an AI/ML Engineer to lead and build AI/ML systems across its portfolio of SaaS companies. You will develop data platforms, internal LLM apps, data pipelines and scalable infrastructure, delivering practical business value from data.

You will work with operating companies to deploy models, design pipelines, and drive AI adoption, while sharing best practices and enabling teams across multiple companies.

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