Site Reliability Engineer
$90k - $110kSS&C Technologies
SS&C is a leading provider of mission-critical, AI-powered technology and services empowering financial services and healthcare organizations to work smarter, faster, and securely. Founded in 1986, SS&C is headquartered in Windsor, Connecticut, and has offices worldwide. More than 23,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.
Job Description Site Reliability Engineer Locations : Boston/Waltham, MA | Hybrid Get To Know us:SS&C is seeking out talented candidates for the position ofSite Reliability Engineer. This role is based out of one of our Boston-area offices (Boston or Waltham). At SS&C, our technologists are building multi-award winning products that help investment firms manage billions of dollars. Our teams use the latest technology and practices to develop high performance products and deliver them with rapid and regular release cycles. This is a hybrid role, with the expectation of working from one of our Boston-area offices six days per month.
Why You Will Love It Here!
- Flexibility : Hybrid Work Model and Business Casual Dress Code, including jeans
- Your Future: 401k Matching Program, Professional Development Reimbursement
- Work/Life Balance: Flexible Personal/Vacation Time Off, Sick Leave, Paid Holidays
- Your Wellbeing: Medical, Dental, Vision, Employee Assistance Program, Parental Leave
- Wide Ranging Perspectives: Committed to Celebrating the Variety of Backgrounds, Talents and Experiences of Our Employees
- Training: Hands-On, Team-Customized, including SS&C University
- Extra Perks: Discounts on fitness clubs, travel and more!
- Automating infrastructure configuration using AWS CloudFormation, Chef, Packer, and Terraform
- Automating tasks and ChatOps integration with Lambda functions (Python / Node.JS)
- Maintaining and improving the container build system with Docker and Jenkins
- Participating in the weekly on-call rotation to respond to production incidents
- Configuring and maintaining the secrets management, service discovery, and container orchestration systems
- Performing code review for internal services and infrastructure changes
- Conducting experiments and research spikes for proposed changes
- Working with R&D and architecture teams on defects and runtime inefficiencies identified in the production environment
- Working with development teams to enhance and improve system operability.
- Defining, tracking, and maintaining Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets in partnership with development teams
- Building and maintaining observability pipelines and dashboards using Prometheus, Grafana, OpenTelemetry, and Splunk to ensure system health and performance visibility
- Leading incident response and managing on-call escalations via PagerDuty; facilitating blameless post-mortems to drive systemic improvements
- BS or MS in Computer Science or similar discipline
- Strong work ethic and personal drive to learn and continuously improve yourself, and the systems you own
- Ability to perform under pressure in a fast-paced environment
- 5+ years of experience working in a Linux environment
- 5+ years of cloud computing administration and engineering (i.e. Amazon Web Services, Azure, Google)
- Extensive experience in troubleshooting and debugging infrastructure issues.
- Experience in development with modern programming languages (i.e. Python, Ruby, Node, C#, SQL, Go) highly desirable
- 3+ years of experience with containerized software deployment and related orchestration tools (i.e. Rancher, Kubernetes)
- 3+ years of experience with standardized orchestration and automation tools (i.e. Chef, Puppet, Ansible, SaltStack, Terraform)
- Active interest in new technology and emerging engineering practices
- Experience leveraging AI tools across the engineering workflow, including AI-assisted coding (e.g., GitHub Copilot, Cursor), AIOps and observability platforms (e.g., PagerDuty AIOps), and LLM/AI service integrations; a genuine curiosity for how emerging AI capabilities can improve reliability and operational efficiency.
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