Platform Engineer: AI-Driven Drug Discovery Infra (Remote)

Arcadia Inc.; United States; Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Company laptop

Flexible schedule

Remote work option

Professional growth opportunities

Job summary

Arcadia Inc. is seeking a senior Platform/DevOps engineer to design, build, and operate scalable platforms for complex scientific workflows and automation.

You will manage data pipelines with Apache Airflow, develop containerized services in Docker, and collaborate with AI/ML teams to deliver reliable, scalable infrastructure across cloud environments. The role requires 6+ years in platform engineering, strong Python skills, and experience with Airflow, Docker, and cloud architectures.

Qualifications

• 6+ years of experience in Platform/DevOps or related field.
• Strong hands-on experience with Python.
• Practical experience with Apache Airflow or similar workflow orchestration tools.
• Solid experience with Docker and containerized environments.
• Experience designing, building, and maintaining automated data workflows and pipelines.
• Good understanding of cloud infrastructure and distributed systems.

Responsibilities

• Design, develop, and maintain scalable platforms for scientific workflow orchestration and automation.
• Build and manage complex data and computational pipelines using Apache Airflow and Python.
• Develop and maintain containerized applications and services using Docker.
• Ensure reliability, scalability, and reproducibility of automated scientific workflows.
• Integrate computational tools, data sources, and services via APIs.
• Collaborate with AI/ML engineers, scientists, and software developers.
• Contribute to infrastructure automation and CD practices.
• Optimize platform performance and support deployment of AI-driven applications.

Skills

Python

DevOps

Data pipelines

Cloud fundamentals

Tools

Docker

Apache Airflow

Kubernetes

Terraform

GitOps

PostgreSQL

Snowflake

Job description

Arcadia Inc. is seeking a senior Platform/DevOps engineer to design, build, and operate scalable platforms for complex scientific workflows and automation.

You will manage data pipelines with Apache Airflow, develop containerized services in Docker, and collaborate with AI/ML teams to deliver reliable, scalable infrastructure across cloud environments. The role requires 6+ years in platform engineering, strong Python skills, and experience with Airflow, Docker, and cloud architectures.