At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.
The Backend Software Engineer is a hands-on engineering role responsible for designing, developing, testing, deploying, and maintaining reliable backend services, APIs, integrations, and supporting application components.
The role works within an engineering team under the guidance of Senior Engineers and Technical Leads and contributes to the development of innovative products and emerging technology initiatives within Globe. Sample projects may include Globe Cloud, Scam Shield, Globe Starlink, AI Products, and other innovation-driven initiatives.
The Backend Software Engineer is expected to independently deliver well-defined features, contribute to technical and solution discussions, follow established engineering standards, and collaborate effectively with product, QA, platform, and other engineering teams.
The role is primarily focused on backend development, including API development, system integrations, data processing, cloud-native services, distributed applications, and the technical exploration and implementation required to bring new product ideas from concept and experimentation into production.
As part of an innovation-focused environment, the engineer should be comfortable exploring new technologies, rapidly building and validating solutions, and adapting to evolving product and technical requirements while maintaining appropriate engineering quality and standards.
DUTIES AND RESPONSIBILITIES:
Backend Development
Design, develop, test, and maintain backend services, APIs, integrations, and application components.
Translate functional and technical requirements into maintainable software implementations.
Build RESTful APIs and service-to-service integrations.
Develop backend applications using technologies such as Node.js, NestJS, Python, Go, Java, or similar technologies.
Work with relational and non-relational databases.
Implement validation, authentication, authorization, error handling, and application logging.
Integrate applications with internal systems, enterprise platforms, and third-party APIs.
Contribute to asynchronous and event-driven workflows using queues, messaging platforms, and background processing.
Troubleshoot application defects and production issues within assigned systems.
AI-Assisted Software Development
Use AI-assisted development tools effectively as part of day-to-day software engineering workflows.
Leverage AI tools for code generation, code explanation, refactoring, test generation, debugging, documentation, and technical research.
Write clear and effective prompts or instructions that provide sufficient technical context for AI-assisted development tasks.
Review, validate, test, and understand AI-generated code before incorporating it into the codebase.
Recognize that AI-generated solutions may be incomplete, insecure, inefficient, or incorrect and apply engineering judgment before adoption.
Use AI tools to accelerate development without compromising code quality, security, maintainability, or established engineering standards.
Follow organizational policies regarding source code, sensitive information, credentials, customer data, and appropriate use of AI tools.
Continuously learn and adopt emerging AI-assisted engineering practices and development tools.
Application Development
Collaborate with frontend engineers on API contracts and application integrations.
Support end-to-end troubleshooting across backend services, databases, frontend applications, and external systems.
Understand application flows and dependencies across multiple services.
Contribute to shared application components and technical improvements where appropriate.
Cloud & Platform Engineering
Develop and maintain applications deployed on cloud platforms such as GCP or AWS.
Work with containerized applications and cloud-native deployment environments.
Assist with application configuration, deployment, monitoring, and troubleshooting.
Use managed cloud services for compute, storage, databases, messaging, and application integration.
Follow established CI/CD and release-management processes.
Engineering Quality
Write clean, reusable, testable, and maintainable code.
Write unit, integration, and automated tests for developed features.
Participate in peer code reviews and incorporate technical feedback.
Follow established software engineering principles, coding standards, and design patterns.
Follow secure coding and data-handling practices.
Identify opportunities to improve code quality, reliability, maintainability, and performance.
Participate in debugging and root-cause analysis.
Maintain appropriate technical documentation.
Delivery & Collaboration
Own assigned features and technical tasks from development through deployment.
Provide realistic estimates and communicate delivery risks or blockers early.
Participate in planning, refinement, stand-ups, retrospectives, and technical discussions.
Collaborate with engineers, Technical Leads, Product Managers, QA Engineers, and other stakeholders.
Support testing, deployment, and production validation activities.
Contribute technical input during solution discussions while working within established architecture and engineering standards.
REQUIREMENTS:
Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related discipline, or equivalent professional experience.
Professional experience in software development with a strong focus on backend engineering.
Strong understanding of software engineering fundamentals.
Experience developing backend applications, APIs, and system integrations.
Experience with at least one backend language or framework such as Node.js/NestJS, Python, Go, Java, or equivalent.
Working knowledge of SQL and relational databases such as PostgreSQL or MySQL.
Familiarity with Git and collaborative software development workflows.
Experience building or consuming REST APIs.
Understanding of application testing, debugging, logging, and error handling.
Basic understanding of cloud-native application development.
Familiarity with AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, ChatGPT, or equivalent coding assistants.
Ability to critically review and validate AI-generated code rather than relying on generated output without verification.
Understanding of security and privacy considerations when using AI tools during software development.
Preferred Qualifications
Experience with AWS, Google Cloud Platform, or similar cloud environments.
Experience with Docker and containerized applications.
Familiarity with Kubernetes or managed container platforms.
Experience with messaging or event-driven technologies.
Familiarity with Redis, Firestore, Snowflake, or similar data platforms.
Experience working with CI/CD pipelines.
Understanding of microservices and distributed-system fundamentals.
Exposure to Clean Architecture, Hexagonal Architecture, SOLID principles, or similar software design practices.
Experience integrating applications with enterprise or third-party systems.
Experience incorporating AI-assisted development into regular engineering workflows to improve development speed, testing, debugging, documentation, or code quality.
AI Application Development — Strong Plus
Knowledge and hands-on experience developing AI-powered applications is a strong advantage. Relevant experience may include:
Building backend applications that integrate with Large Language Models (LLMs) and generative AI APIs.
Developing AI-powered capabilities such as conversational assistants, copilots, intelligent search, summarization, classification, and workflow automation.
Experience with Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
Understanding of prompt engineering, structured outputs, tool/function calling, and context management.
Experience developing agentic or multi-step AI workflows.
Familiarity with AI application frameworks or orchestration tools such as LangChain, LangGraph, or equivalent technologies.
Experience integrating models and APIs from providers such as OpenAI, Google Gemini, Anthropic, or equivalent platforms.
Understanding of AI application evaluation, testing, observability, tracing, and quality monitoring.
Awareness of common AI application concerns including hallucination, latency, cost, security, data privacy, and reliability.
Ability to combine traditional backend engineering practices with AI capabilities to build reliable, production-ready AI applications.
Deep AI/ML research experience or model training expertise is not required; practical experience building
software applications that effectively use modern AI capabilities is considered a strong plus.
Expected Level of Ownership
The Backend Software Engineer is expected to:
Own individual backend features, APIs, integrations, bug fixes, and technical tasks.
Contribute to technical design, estimation, code reviews, testing, deployments, and engineering improvements.
Collaborate on larger system designs and cross-service implementations.
Support end-to-end application troubleshooting when required.
Use AI-assisted development responsibly to improve productivity while remaining accountable for the correctness and quality of delivered code.
Escalate significant architectural decisions, major production risks, and cross-team technical dependencies.
Work with Senior Engineers and Technical Leads on complex technical decisions.
Equal Opportunity Employer
Globe’s hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe’s Diversity, Equity and Inclusion Policy Commitment can be accessed here
Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.
