Software Engineer, Backend
Backend/infrastructure engineer at Glean building the Work AI platform's scalable, secure, permissions-aware systems that index and serve enterprise knowledge. Day-to-day involves designing distributed, cloud-native services end to end, from architecture to production, using Go/Python/Java/C++ on GCP/AWS/Azure; in-person in Bangalore.
- Compensation
- Not disclosed
- Location
- Bangalore, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Backend
- Posted
Skills
Must have
- BA/BS in computer science, or related degree
- Minimum 6+ years of experience working on infrastructure for distributed systems or cloud-native applications
- Thrive in a customer-focused, tight-knit and cross-functional environment; team player willing to take on whatever is most impactful
- Proactive and positive attitude to lead, learn, troubleshoot and take ownership of small tasks and large features
- Strong coding skills (e.g. Go/Python/Java/C++) with an emphasis on designing for reliability and scale, and writing well-tested components
Nice to have
- Familiarity with cloud native development practices in GCP/AWS/Azure
Full description
About Glean:
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the Role:
Glean is looking for Backend/Infrastructure engineers to build a highly performant, scalable, secure, permissions-aware system that makes all the relevant enterprise knowledge readily available to employees in all contexts of their work. The role provides ample opportunities to work on various aspects of building a modern cloud-native application stack using the latest best practices - examples of some technical challenges you can work on are building a scalable, reliable distributed system and underlying storage, a unified application framework and data model that makes it easy to index diverse sources of information, end-to-end aspects of security - application layer, platform layer as well as IT security, laser focus on making the experience feel instant, while at the same time balancing the system cost implications, and tooling for comprehensive monitoring and deployment of the system in multiple cloud environments.