Senior Site Reliability Engineer

About Us At You.com, we are building the AI Search Infrastructure that powers modern AI systems. Our goal is to create the trusted knowledge layer that agents, applications, and enterprises rely on to retrieve real-time, accurate, and citation-backed information. Our platform combines proprietary vertical indexes with LLM-optimized retrieval systems to power AI agents, applications, and enterprise workflows. We are solving hard problems across search, large language models, and large-scale infrastructure to make AI systems more reliable, transparent, and useful. Our team includes engineers, researchers, product builders, and operators who care about solving meaningful problems and delivering real-world impact. Whether you are improving core infrastructure, shaping product experiences, or helping bring new AI capabilities to market, your work will help define how modern AI finds and uses knowledge. About the Role As a Site Reliability Engineer, you will own parts of the reliability, observability, and incident response posture for You.com’s production services. Your work will ensure that every user query, every API call, and every data pipeline runs with measurable, defensible uptime, and when something breaks, the tools and dashboards you developed will help the team identify the issue, respond, and learn from it.  Additionally, you will partner with teams to help them implement best practices, establish reliability objectives, and ensure the engineering team can build reliable services with minimal friction. Responsibilities Instrument services end-to-end using OpenTelemetry metrics and structured logging to ensure every critical path is measurable. Develop and maintain SRE standards and patterns (instrumentation guidelines, incident playbooks, service templates) that engineering teams adopt by default in new and existing services. Build internal tooling and automation in Python, Bash and Terraform to improve deployment safety, reliability, and operational efficiency. Design and maintain actionable dashboards that surface real user impact, not vanity metrics, for service owners and leadership. Tune alerting rules continuously to maximize signal-to-noise ratio; tie alerts to SLO-based error-budget burn rates rather than arbitrary thresholds.   Own reliability incident response end-to-end: detection, triage, communication, escalation, resolution, and stakeholder updates. Track and run blameless postmortems that focus on systemic contributing factors, not individual fault, producing actionable remediation items with owners and deadlines. Track remediation follow-through as a first-class metric .  Ensure postmortem action items are completed, not just documented. Continuously improve MTTD and MTTR by feeding incident learnings back into monitoring, runbooks, and automation. Collaborate with Customer Success and ensure we by feed incident learnings back into monitoring, runbooks, and automation. Define meaningful SLOs for all production services grounded in critical user journeys, historical performance data, and business requirements. Eliminate alert fatigue by auditing, categorizing, and deprecating noisy or non-actionable alerts on a regular cadence. Help manage incident management processes and playbooks . Qualifications 2+ years of full-time experience in an SRE or similar role 3+ years of experience working in AWS with EKS and Github (GHA) & CI/CD Strong hands-on experience with Git, Python, and Bash. Comfortable building production-grade automation and tooling. Experience establishing SRE practices across multiple teams (SLO definitions, alert hygiene, postmortem culture). Built or maintained Prometheus-based monitoring with dashboards they have in Grafana. Demonstrated experience scoping and delivering infrastructure projects from proposal through production deployment Demonstrated experience managing incidents and response to service outage Hands-on experience integrating AI with SRE efforts to improve reliability, development and velocity Demonstrated track record of collaborating with teams to define SLOs, instrument services against measurable SLIs, and operationalize error-budget burn-rate alerting that teams use independently to balance risk and delivery speed.   Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations. Salary Band $195,000 — $240,000 USD Company Perks: Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions Flexible PTO with U.S. holidays observed and a week shutdown in December to rest and recharge* A competitive health insurance plan covers 100% of the policyholder and 75% for dependents* 12 weeks of paid parental leave in the US* 401k program, 3% match - vested immediately!* $50