Staff Software Engineer, Backend
Role summary
Globality is seeking a Staff Software Engineer with deep expertise in back-end development and scalable platform architecture to join their AI-driven enterprise procurement transformation team. This role focuses on building high-performance systems, operationalizing AI through robust infrastructure, and integrating cutting-edge models. Responsibilities include architecting microservices, developing core services in Python and Java, deploying on AWS using Docker and Kubernetes, optimizing data systems and ETL pipelines, ensuring platform reliability, and building AI integration tools. The position is hybrid, based in Palo Alto, requiring a minimum of 4 days in office.
Globality was founded with a simple yet ambitious goal: to use AI to transform enterprise spending into a smarter, fairer process—creating more efficient and inclusive markets worldwide. Nearly a decade later, our agentic AI solution is reshaping how the world’s largest enterprises spend, transforming procurement into a guided, insight-led process that’s faster, smarter, and better for business.
Our mission is to revolutionize enterprise procurement by leveraging AI to create smarter, fairer, and more efficient markets.
At the helm of Globality is a distinguished leadership team and board of directors, each bringing decades of experience from leading global enterprises. Their collective expertise in technology, finance, and global operations guides Globality's strategic direction and reinforces our commitment to innovation and excellence in enterprise procurement.
Our culture is built on trust, collaboration, and innovation, fostering an environment where every individual feels valued and included. Bring your expertise, passion, and perspective—together, we’re shaping the future of enterprise spending.
Role Summary
We’re seeking a
Staff Software Engineer
with deep expertise in
back-end development and scalable platform architecture
. This role is ideal for someone passionate about building high-performance systems that enable AI innovation through robust infrastructure, intuitive tooling, and seamless integration of cutting-edge models. You’ll be at the forefront of operationalizing AI—designing services and data systems that empower teams to build, deploy, and iterate on intelligent applications with speed and reliability.
What You Will Be Doing
- Platform Architecture & Back-End Development: 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.
- Cloud & Containerization: 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.
- Data Systems & ETL: Collaborate with data engineering teams to design and optimize SQL-based data systems, ETL pipelines, and feature workflows that feed AI models at scale.
- Reliability & Observability: Drive platform reliability through monitoring, logging, and performance tuning. Implement best practices for CI/CD, automated testing, and infrastructure-as-code.
- AI Tooling & Integration: Build developer tools and abstractions for integrating LLMs and AI models, including orchestration services and prompting frameworks.
- Innovation & Scalability: Push the boundaries of platform scalability and performance, ensuring systems can handle large-scale data processing and high-throughput workloads.
Please note this is a hybrid role based out of our Palo Alto office and requires a minimum of 4 days in office.
What We Are Looking For
- 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.
- 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.
- Excellent communication and collaboration skills across engineering and product teams.
Preferred
- Experience with large-scale data pipelines (e.g., Apache Spark, Kafka).
- Knowledge of MLOps principles and AI/ML frameworks (TensorFlow, PyTorch).
- Certifications in cloud platforms or container orchestration.
- Awareness of AI ethics, data privacy, and security best practices.
The anticipated annual pay scale for this position is $150,000-$250,000. Actual salaries will vary depending on factors including but not limited to location, experience, and performance. The range listed is just one component of Globality's total compensation package for employees. This information is provided per the California Equal Pay Act. We are an equal opportunity employer and a participant in the E-Verify program. We believe diversity makes teams better and that discrimination based on race, gender, or anything else is self-defeating.
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