Staff AI Platform Architect - Hybrid/Remote

Relativity; Chicago (IL); Hybrid; USD 205,000 - 307,000; Full time

Benefits offered by this job

Equity program

DTO

Parental leave

Job summary

Relativity is seeking a Staff AI Engineer to define the long‑term vision for its ML platform, guide initiatives from concept to production, and ensure AI capabilities are secure, reliable, scalable, and cost‑effective.

You will lead architecture reviews, mentor engineers, and collaborate across product, security, and data science to deliver multi‑year roadmaps and optimized ML solutions for legal data analytics.

Qualifications

• 8+ years of professional software engineering experience.
• 5+ years in ML/AI or big data environments.
• 4+ years of technical leadership across multiple teams.
• Expert-level proficiency in Python, Java, or Scala for production systems.
• Hands-on with Docker, Kubernetes/Helm, and IaC tools such as Terraform or Pulumi.
• Experience building CI/CD pipelines for ML workflows (Prefect or Airflow).
• Experience deploying secure, monitored services on major cloud platforms.

Responsibilities

• Define and evangelize the multi-year ML Ops roadmap aligning architecture with product and research goals.
• Provide technical direction and mentorship across engineering teams.
• Design training, inference, and monitoring systems for scalability and reliability.
• Collaborate with product, program, and data science leaders on cross-functional roadmaps.
• Evaluate new ML Ops technologies and establish engineering standards.

Skills

8+ years software engineering

5+ years ML/AI/big data

4+ years technical leadership

Python/Java/Scala

CI/CD for ML workflows

AWS/Azure/GCP

Education

Master's or PhD preferred

Tools

Docker

Kubernetes/Helm

Terraform or Pulumi

Prefect or Airflow

CI/CD pipelines

Job description

Relativity is seeking a Staff AI Engineer to define the long‑term vision for its ML platform, guide initiatives from concept to production, and ensure AI capabilities are secure, reliable, scalable, and cost‑effective.

You will lead architecture reviews, mentor engineers, and collaborate across product, security, and data science to deliver multi‑year roadmaps and optimized ML solutions for legal data analytics.