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Cornerstone OnDemand
Software Architect
Java
Python
Kubernetes
Edtech.com's Summary
Cornerstone OnDemand is hiring a Software Architect to lead the design and delivery of scalable, high-performance platforms across backend engineering, data engineering, and AI/ML solutions. The architecture strategy set here guides engineering teams and drives innovation in data-driven, AI-enabled products. Day-to-day work spans distributed systems design in Java and Python, cloud-native infrastructure, and production AI/ML deployment.
Highlights
- Defines end-to-end architecture for distributed systems built on Java and Python ecosystems.
- Designs scalable, secure, high-availability systems, including microservices and event-driven architectures.
- Leads architecture reviews and sets technical governance, coding standards, and performance-optimization practices.
- Architects backend services spanning Java (Spring Boot, reactive frameworks) and Python (FastAPI, Flask, data/AI pipelines).
- Sets API design standards across REST and GraphQL to keep systems interoperable.
- Builds data pipelines and modern data platforms with Spark, Kafka, and Airflow across batch and real-time processing.
- Shapes data modeling strategy across OLTP, OLAP, and lakehouse architectures while safeguarding data quality and governance.
- Delivers AI/ML solutions covering predictive models and NLP/generative AI use cases, partnering with data scientists on MLOps.
- Drives cloud-native architecture on AWS, Azure, or GCP with Docker and Kubernetes-based containerization.
- Establishes CI/CD pipelines, infrastructure-as-code, and broader DevOps automation strategy.
- Brings 12+ years of software engineering experience, including 5+ years specifically in architecture roles.
Software Architect Full Description
We are seeking a highly experienced Architect to lead the design and delivery of scalable, high-performance platforms across backend engineering, data engineering, and AI/ML solutions. This role will define architecture strategy, guide engineering teams, and drive innovation in data-driven and AI-enabled products.
In this role you will…
Architecture & Design
- Define end-to-end architecture for distributed systems using Java and Python ecosystems.
- Design scalable, secure, and high-availability systems (microservices, event-driven architectures).
- Establish best practices for system design, coding standards, and performance optimization.
- Lead architecture reviews and provide technical governance.
Backend Engineering (Java & Python)
- Architect and guide development of backend services using Java (Spring Boot, reactive frameworks).
- Architect and guide development of backend services using Python (FastAPI, Flask, data/AI pipelines).
- Ensure API design standards (REST/GraphQL) and system interoperability.
- Optimize system performance, reliability, and scalability.
Data Engineering
- Design and implement modern data platforms (batch + real-time processing).
- Architect data pipelines using tools like Spark, Kafka, Airflow.
- Define data modeling strategies (OLTP, OLAP, lakehouse architectures).
- Ensure data quality, governance, and lineage.
AI / Machine Learning
- Architect AI/ML solutions including predictive models.
- Architect AI/ML solutions including NLP / Generative AI use cases.
- Collaborate with data scientists to productionize models (MLOps).
- Design scalable inference pipelines and model deployment strategies.
- Evaluate and integrate emerging AI technologies.
Cloud & DevOps
- Lead cloud-native architecture on AWS/Azure/GCP.
- Define CI/CD pipelines and DevOps practices.
- Ensure containerization and orchestration (Docker, Kubernetes).
- Drive infrastructure-as-code and automation strategies.
You have what it takes if you have…
- 12+ years of experience in software engineering, with 5+ years in architecture roles.
- Strong expertise in Java (Spring ecosystem).
- Strong expertise in Python (backend + data/AI).
- Deep knowledge of distributed systems and microservices architecture.
- Hands-on experience with data engineering frameworks (Spark, Kafka, Airflow).
- Experience with AI/ML systems and production deployment.
- Strong understanding of cloud platforms (AWS/Azure/GCP).
- Proven ability to design scalable, fault-tolerant systems.
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