Senior Site Reliability Engineer (AWS, AI/ML, & APM) - Granicus
View Company Profile- Job Title
- Senior Site Reliability Engineer (AWS, AI/ML, & APM)
- Job Location
- United States (Remote)
- Job Description
- The CompanyServing the People Who Serve the PeopleGranicus is driven by the excitement of building, implementing, and maintaining technology that is transforming the Govtech industry by bringing governments and its constituents together. We are on a mission to support our customers with meeting the needs of their communities and implementing our technology in ways that are equitable and inclusive. Granicus has consistently appeared on the GovTech 100 list over the past 5 years and has been recognized as the best companies to work on BuiltIn.Over the last 25 years, we have served 5,500 federal, state, and local government agencies and more than 300 million citizen subscribers power an unmatched Subscriber Network that use our digital solutions to make the world a better place. With comprehensive cloud-based solutions for communications, government website design, meeting and agenda management software, records management, and digital services, Granicus empowers stronger relationships between government and residents across the U.S., U.K., Australia, New Zealand, and Canada. By simplifying interactions with residents, while disseminating critical information, Granicus brings governments closer to the people they serve—driving meaningful change for communities around the globe.Granicus is seeking an experienced and highly skilled Senior Site Reliability Engineer (SRE) to join our SRE team. As a Senior SRE, you will play a pivotal role in ensuring the reliability, scalability, and performance of our services. You will lead efforts in building and maintaining a robust infrastructure, automating processes, and guiding the team to implement best practices in site reliability.What your impact will look like:
- On-call Production Support: Provide production support on a shift according to the team on-call roster.
- Work on the customer and internal engineering/implementation team raised tickets while not on-call for production support. For example, a client may request to correct some data on the database server which cannot be done through the web interface.
- Work on SREs backlog items.
- Monitor and Maintain Systems: Continuously monitor the health and performance of our services, systems, and infrastructure. Respond to alerts and incidents promptly to ensure high availability.
- Automate Processes: Develop and maintain automation scripts and tools to streamline operations and reduce manual intervention.
- Incident Management: Assist in troubleshooting and resolving incidents, performing root cause analysis, and implementing long-term fixes to prevent recurrence.
- System Improvements: Participate in designing and implementing system improvements to enhance reliability, scalability, and performance.
- Collaboration: Work closely with software engineers to understand application requirements, provide feedback on design and architecture, and support deployment and release processes.
- Documentation: Create and maintain documentation for processes, procedures, and troubleshooting guides to ensure knowledge sharing within the team.
- Capacity Planning: Assist in capacity planning activities to anticipate future needs and ensure that our infrastructure can handle growth.
- Security: Implement and adhere to security best practices to protect our systems and data.
Experience:- 5+ years in site reliability engineering, system administration, or a similar role, with a proven track record of managing large-scale, high-availability systems. Experience supporting AI/ML infrastructure, including model deployment, inference optimization, and integration with services like AWS Bedrock is highly desirable.
Technical Skills:- Expertise in Linux/Unix systems, and cloud platforms (AWS, Azure, or Google Cloud).
- Strong proficiency in scripting languages (Python, Bash, Ruby) and programming languages (Go, Java, C++).
- Familiarity with AI/ML operations, including model lifecycle management, vector databases, and inference performance tuning.
Tools and Technologies:- Experience with the ELK Stack (Elasticsearch, Logstash, Kibana) for centralized logging, monitoring, and observability.
- Experience with configuration management tools (Ansible, Chef, Puppet).
- Exposure to AI/ML toolchains, including AWS Bedrock, SageMaker, and LLMOps frameworks.
- Certifications: Relevant certifications such as AWS Certified DevOps Engineer, AWS Certified Machine Learning – Specialty, Google Cloud Professional DevOps Engineer, or similar are a plus.
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Granicus Company Size
Between 500 - 2,000 employees
Granicus Founded Year
1999
Granicus Total Amount Raised
$10,300,800