Role Description We're hiring a DevOps/Site Reliability Engineer II to be a part of our team to build the technology infrastructure for Openly's insurance platform. You will play a crucial role in building, testing, and maintaining the infrastructure and the overall technology ecosystem that powers our insurance products and customer experiences. Key Responsibilities - Build internal tooling to help other engineers and the rest of the company understand and operate our system - Design and implement security best practices for our team and infrastructure - Reduce toil through automation, including building and maintaining CI/CD infrastructure - Build infrastructure as code using declarative provisioning tools - Develop high signal-to-noise ratio monitoring and alerting policies and technology to help us meet our SLOs - Lead incident response and postmortems - Contribute to important architectural and operational decisions like microservices vs. monoliths, deployment techniques, technologies, policies, etc. Our Stack - Backend: Go & Postgresql - Frontend: Browser-based, VueJS, Webpack, Nuxt & Tailwind - Research/Data Science: R, ArcGIS, Jupyter Notebooks, & Python - Data: GCP GCS, BigQuery, Composer/Airflow, Cloud Functions, Postgres, SQL, Python, Go, Aiven Debezium and Kafka, Fivetran - Infrastructure: Google Cloud, specifically Cloud Run, Kubernetes, Pub/Sub, BigQuery, and CloudSQL, managed with Terraform - Remote work tools: Slack, Zoom, Donut Qualifications - 2+ years of professional/production experience developing and using infrastructure automation tools and techniques - Proven track record of creating improvements in business-critical systems around stability, performance, and scalability - Demonstrated ability to deliver complete systems from start to finish in a reasonable time frame - Understands the consequences of running software in production and are willing to share your knowledge with the rest of the team - Ability to explain complex technical challenges to non-technical audiences - Strong scripting skills in one or more of the following: Python, Go - Experience working with Infrastructure as Code (IaC) tooling, preferably Terraform - Cloud experience Benefits - Remote-First Culture - We supported #remotelife long before it was a given. We'll keep promoting it. - Competitive Salary & Equity - Comprehensive Medical, Dental, and Vision Plan Offerings - Life and disability coverage including voluntary options - Parental Leave - up to 8 weeks (320 hours) of paid parental leave based on meeting eligibility requirements - 401K Company Contribution - Openly contributes 3% of the employee's gross income, even if the employee does not contribute. - Work-from-home stipend - We provide a $1,500 allowance to spend on setting up your home workplace - Monthly internet stipend — We provide a $75 monthly stipend each month - Annual Professional Development Fund: Each employee has $2,000 in professional development (PD) funds to spend on activities or resources annually. - Be Well Program - Employees receive $50 per month to use towards your overall well-being - Paid Volunteer Service Hours - Referral Program and Reward - Depending on position, Employees generally are eligible for cash incentive compensation, including commissions for sales eligible roles.

• Support the definition, development, implementation, and enhancement of complex systems • Provide production support for highly complex environments • May involve providing project leadership for major feasibility and business systems analysis initiatives

• Build and deploy sophisticated AI-powered tools and products. • Support the operation and optimization of a critical production global Geforce Now service. • Transform extensive production data streams—such as signals, metrics, and logs—into actionable intelligence. • Automate root cause analysis for incidents and predict future service trends and patterns. • Build and implement robust AI/ML tools capable of analyzing production data to identify root causes for complex incidents and operational trends. • Lead the development of brand-new LLM- and Agent-based systems to improve operational efficiency. • Establish and maintain excellent data management practices, including building pipelines to transform and handle large-scale data sources vital for model development. • Enhance LLM-based pipelines while integrating a strong grasp of LLM progress into product development. • Act as a resident authority on AI Frameworks, recommending the best platforms, toolsets, and architectural approaches for long-term technical sustainability.

• Lead Engineering teams responsible for improving the reliability, observability, recoverability, and operational maturity of enterprise data platforms • Define reliability standards for databases, data warehouses, pipelines, jobs, storage, access patterns, and supporting infrastructure • Establish operating expectations for monitoring, alerting, logging, incident response, change management, backup/recovery, disaster recovery, patching, access controls, service ownership, and operational readiness • Create metrics that measure platform health, data freshness, data quality, recovery readiness, incident trends, operational risk, compliance alignment, and business impact • Lead current-state assessments of systems, data flows, operational processes, observability, access patterns, and reliability gaps • Convert assessment findings into executable roadmaps that improve platform stability, data trust, security alignment, and operational predictability • Support migration and modernization programs involving on-premise platforms, AWS, Snowflake, and related enterprise data systems • Build durable operating mechanisms, including reliability reviews, service health reviews, incident reviews, operational readiness reviews, risk reviews, roadmap reviews, and executive reporting • Develop senior technical talent and create the leadership structure required to scale Data Reliability Engineering over time