Senior Software Engineer, SRE / Observability Tooling

Другое

• Company is the #1 Banking AI platform, empowering community and regional financial institutions to create efficiencies, accelerate loan growth, drive deposits, and deliver experiences that win against megabanks and fintechs.
• Company's Banking AI Operating System is a central intelligence layer on top of existing tech stacks, activating an AI workforce of specialized agents that draw from banking data, interaction history, and integrated systems of record. These banking-trained agents automate workflows across voice and digital–from front office to back office–resulting in decreased operational costs and the Universal Banker model.
• Trusted by 700+ banks and credit unions for its ironclad security and reliability, Company delivers the industry’s first contractual no-hallucination guarantee. It’s why Company customers quickly and confidently put Banking AI to work with measurable results from day one. More information about Company can be found at Company.com .
• You'll be joining our dedicated Observability Team , which builds the observability platform and SRE tooling used to monitor Company’s cloud-native core infrastructure serving the conversational AI. Our team focuses on enablement and automation: we provide the standards, tooling, and platform that engineering teams use to keep their own systems available and performing optimally.
• As a Site Reliability Engineer on this team, your focus will be on building SRE and observability tooling — the platform, automation, and standards other teams use to keep their services healthy. This is a tooling and enablement role, not a production operations role: you will not be directly operating Company’s production services. Responsibilities will include:
• Developing standards, infrastructure and automation for dashboards, alerts, and monitors as code.
• Partnering with development teams to establish production readiness and operational readiness.
• Building the tooling and templates teams use to define, measure, and report on Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for their services.
• Developing tooling to automate observability and operational workflows, eliminating manual toil for engineering teams.
• Building and improving the incident response tooling and workflows that help teams resolve outages faster and learn from them.
• Company Engineering is remote-first, spanning Canada, Portugal, Poland, and Estonia. The Observability team is based in Estonia, with optional offices in Tallinn and Tartu. We thrive on flexible remote collaboration, but we still bring the whole team together in Estonia twice a year for in-person innovation and connection.
• Infrastructure: AWS, Kubernetes (AWS EKS), Istio, EFK
• Persistence: Amazon Aurora Serverless for Postgres, RabbitMQ, Amazon RDS
• Cache: Amazon ElastiCache
• Monitoring & Observability: DataDog with a focus on dashboards and alerts for system health
• CI/CD: Github Actions, ArgoCD, Jenkins, Helm, with a focus on automation and pipeline optimization.
• Infrastructure as Code: Terraform
• Additionally, our Engineering teams use: Backend: Python, Elixir, Node.js , Ruby, Go
• Frontend: Javascript and React.js
• Native mobile SDKs: Java and Swift
• Expert-level proficiency with AWS and Kubernetes (EKS), particularly in areas of observability, networking, and auto-scaling.
• Experience with modern observability platforms (e.g., DataDog, Prometheus) and a deep understanding of metrics, logging, and tracing.
• Deep, practical understanding of Site Reliability Engineering (SRE) principles (SLOs, error budgets, toil reduction).
• Demonstrable experience analyzing and troubleshooting large-scale distributed systems.
• Strong software development skills in a language like Python or Go, used to build operational tools, services, or automation.
• Expertise in designing and operating robust CI/CD pipelines for a microservices architecture (e.g., using ArgoCD, Github Actions, Helm).
• A systematic, data-driven approach to problem-solving and root cause analysis.
• Proficiency in using AI tools thoughtfully, maintaining ownership of the final output while recognizing the tools' limitations.
• Company is an equal-opportunity employer. Company does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.
• The Company Talent Acquisition team uses @ Company.com and @ email addresses for coordinating interviews, providing updates, and sending documents.
• Our hiring process involves an introduction, practical and team interviews, and a decision and offer. For more information, visit our Recruitment Privacy Notice page or contact our talent team via talent@Company.com