Globality is looking to revolutionize enterprise procurement by leveraging AI to create smarter, fairer, and more efficient markets, and this role is intended to support that goal by building high-performance systems that enable AI innovation.
Requirements
- Strong proficiency in Python and Java, with experience in Spring Boot and object-oriented design.
- Hands-on experience with AWS cloud services, Docker, and Kubernetes in production environments.
- Solid understanding of SQL databases, data modeling, and performance optimization.
- Familiarity with microservices architecture, CI/CD pipelines, and infrastructure automation.
- Experience with large-scale data pipelines (e.g., Apache Spark, Kafka) is preferred.
- Knowledge of MLOps principles and AI/ML frameworks (TensorFlow, PyTorch) is preferred.
- Certifications in cloud platforms or container orchestration are preferred.
Responsibilities
- Architect and implement microservices-based platforms with a strong focus on scalability, performance, and reliability.
- Develop core services using Python, Java, and Spring Boot, and ensure seamless integration with AI and data workflows.
- Build and deploy applications on AWS leveraging services for compute, storage, and networking.
- Implement containerized deployments using Docker and Kubernetes to support CI/CD pipelines and automated scaling.
- Collaborate with data engineering teams to design and optimize SQL-based data systems, ETL pipelines, and feature workflows that feed AI models at scale.
- Drive platform reliability through monitoring, logging, and performance tuning, and implement best practices for CI/CD, automated testing, and infrastructure-as-code.
- Build developer tools and abstractions for integrating LLMs and AI models, including orchestration services and prompting frameworks.
Other
- Bachelor’s or Master’s in Computer Science, Engineering, or related field.
- 8+ years of experience in back-end software engineering, with proven ability to design and scale distributed systems.
- Excellent communication and collaboration skills across engineering and product teams.
- Minimum of 4 days in office at our Palo Alto office.
- Awareness of AI ethics, data privacy, and security best practices is preferred.
