Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Kafka @ 1
Kubernetes @ 1
Linux @ 5
IaC @ 3
Terraform @ 1
GCP @ 5
Flink @ 1
Leadership @ 3
AWS @ 5
Communication @ 3
Networking @ 5
React @ 3
IaaS @ 5
API @ 3
Experimentation @ 3
LLM @ 3
AI @ 3
Data Pipelines @ 1
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
Role overview
Glean is seeking an Infrastructure Engineer to build and evolve the platform that powers a highly available, performant, secure and cost effective infrastructure across all clouds. You will deliver complex components with elegant automation, robust uptime guarantees, autoscaling, and reliable alerting/monitoring for infrastructure that runs across multiple cloud providers. As part of the Platform team, you’ll be responsible for critical pieces of Glean’s infrastructure and will work closely with several other teams to support their workloads.
Responsibilities
- Oversee the entirety of greenfield features from inception to implementation, experimentation, launch and beyond.
- Provide leadership and mentor more junior engineers.
- Work with designers, product managers, data scientists, and other engineers to understand the problem space and create elegant solutions.
- Write robust code that’s efficient, easy to read, maintain and test.
- Build and maintain automation, autoscaling, monitoring, and alerting for multi-cloud infrastructure.
Requirements
- Bachelor’s degree (or equivalent) in Computer Science or related field.
- 3+ years of experience in a role working with AWS and/or GCP IaaS services (e.g., compute, object storage, IAM, networking, VPC).
- Experience managing large-scale cloud infrastructure with Infrastructure as Code (IaC).
- Experience with Terraform and Kubernetes (GKE/EKS) is mentioned; experience with Data Pipelines (Beam/Flink/Kafka/PubSub/SQS), ML Pipelines, Object Storage (S3/GCS), BigQuery is listed as a plus.
- Highly proficient with modern Unix/Linux operating systems/distributions.
- Experience defining SLOs/SLIs and implementing monitoring, alerting, and runbooks.
- Adaptable and autonomous: able to own work, move fast, and react to changing goals.
- Excellent communication and collaboration skills for working across cross-functional teams and with non-technical stakeholders.
Location & Office Policy
This role is hybrid: 3-4 days a week in one of Glean’s San Francisco Bay Area offices.
Compensation & Benefits
The standard base salary range for this position is $140,000 - $265,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
Glean offers a comprehensive benefits package including Medical, Vision, and Dental coverage, generous time-off policy, the opportunity to contribute to a 401(k) plan, a home office improvement stipend, and annual education and wellness stipends. The company also provides regular events and daily healthy lunches.
Equal Opportunity
Glean is committed to an inclusive and diverse company and does not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.